Academic literature on the topic 'Household projection'

The headship rates method (HRM) of household projections based on the share of household heads in the total population of the same demographic characteristics (age, sex, nationality, marital status, etc.) is the most commonly used method, especially by statistical institutes and planning institutions. The specific rates of household heads by age are calculated by dividing the number of household holders of a certain age with the total number of residents of the appropriate age. The future number of households is then simply projected on the basis of population projections by age and assumptions about the future changes of HR. The HRM is based on the projection of the future age structure of the population. In that sense, the choice of methods of population projection, as well as the method of projecting HR-s have determining impact on the outcome of household projections. Given the methodological inconsistency typical for official population projections in Serbia and significant differences in addressing uncertainty of the future population change between deterministic and probabilistic approach in making population projections, the decision to use a probabilistic projection of the population of Serbia as the basis for calculating the future number of house-holds and their structure according to the age of the household head proved to be a logical choice. However, as the basic aim of this article is to show the simple method of household projections, the above-mentioned stochastic projection is used in utterly deterministic manner. The median of the prediction interval of the population distributed across age is interpreted as the most probable future, or as a prognosis. The HR-s based on the age structure estimates and estimated number of households by age of the household head from Household budget survey (HBS) are used for the purpose of HR projecting so that the number of observations would be large enough for calculating inclination parameters. The obtained rates show a tendency to decline during the observed period, however, in certain age categories, the rates are expressed by extreme values that are certainly the result of random sampling in the HBS for the purpose of analyzing consumption rather than analyzing the demographic characteristics of households, and must be taken with a certain reserve. Although the tendency of declining rates in most age categories is not unexpected, surely the intensity of decline is unexpected. For this reason, in the formation of the regression function, the extreme values of the rates are intentionally excluded in the following way: after calculating the regression line parameters, all the values of the rates that deviate from the regression values by more than 20 per cent are rejected, after which the regression parameters are recalculated. On the basis of the second calculation of the regression line, parameters are obtained. However, as the obtained parameters led to unexpectedly large HR changes according to the age of the household head until the end of the projection period (2040), it was assumed that the inclination parameter (b) would be reduced by 10 per cent annually compared to the start year of the regression line. On the basis of the rates according to the 2011 census data and the hypothesis on the slowdown of the observed trends in the future, future HR-s are calculated. Furthermore, based on the projected HR-s by age and future age structure of the population, the number of households by the age of the household head for the projection years is calculated. Based on the results of the projection, the total number of households will be reduced on average by over 11 thousand households per year. Also, compared to the 2011 census, it can be expected that the number of households in all age groups will be reduced by the end of the projection period, except in the category of household heads aged 65 and over that stabilizes to around 900 thousand households by the end of the projection period. Due to the decline in the number of households, the average household size will be reduced by 0.18 members in 2040 compared to 2011, from 2.89 to 2.71. The largest number of households in Serbia are family households, the share of single person households in the population under the age of 50 is small, and the structural barriers to the establishment of an indigenous household in persons under the age of 30 are significant. All of this makes it difficult to withdraw parallels with other European populations in terms of a possible path that the population and households in Serbia should follow in the projection period. Some of the projections of households produced by the HRM of a newer date for populations also found in the post-transition demographic stage show that the age at which the household is based, the mechanisms that affect the generation, change, and extinguishing of the household, which are characteristic for each society, result in significantly different values of age-specific HR-s. Of course, HR-s by age vary considerably among different populations. It is obvious that the key differences in Serbia in relation to other countries occur precisely at the age when individuals base their own household. The existence of postponing marriages and parenting that is recognized as key life-changing milestones in the transition to adulthood and the founding of one?s own household, the chronic lack of systematic housing policy towards young people and high youth unemployment are the main causes of the late establishment of their own household and the maintenance of low HR-s for persons under 30 years of age in Serbia. Nevertheless, during the first decade of the 21st century, there is a certain shift in the financial independence of young people, which gives some hope that in the future HR-s in the category between the ages of 30 and 39 can be slightly increased, which is confirmed on the basis of the sample of households from the HBS for the period 2006-2013. Namely, the tendency of a slight increase in the value of the rate for persons aged between 30 and 39 years is certainly the result of an increase in the age at which the household is based, which can be noticed on the basis of the reduction in rates for persons under the age of 30. On the other hand, a certain decline in the value of the rate characteristic for the households of the holders in their middle age (between 40 and 64 years of age) has an explanation in the increase in number and share of multi-family households in the period 1991-2011, especially in urban areas. During the 1990s, in the conditions of a deep socio-economic crisis, with the continuation in the next decade during the transition of the economic system, in conditions of significant poverty and the phenomenon of the retraditionalization of partnership arrangements within multi-family households, it is obvious that a significant number of families in the middle of their life cycle lived in within parental households whose carriers are aged 65 and over. In fact, as the increase in the HR-s during the thirtieth year of age is the result of deprivation of rates in younger persons, this is, by and large, a rise in rates for persons aged 65 and over due to a reduction in rates among carriers aged between 40 and 64 years. The presented method of household projections is not characterized by methodological sophistication, elegance and precision in reflecting changes in the structure of households according to the family composition and a detailed presentation of changes in the family status of individuals, but it certainly represents an simple way of household projecting according to the age distribution of carriers, the average size and the number of households. It seems that this approach, based on the stability of age-specific rates of household heads, without getting involved in the field of sociology, is quite precise in the medium term, especially given the simplicity in household projecting based on HRM.

Conventional population projections regard individuals, rather than households, as population units of reference. Such an approach has been questioned on both methodological and empirical grounds. Furthermore, in applications to smaller populations, conventional population projections have repeatedly yielded poor results. The simultaneous projection of population and households, on the other hand, regards households as population units of reference, but, in applications based on the notion of the household composition matrix, it has occasionally yielded analytically infeasible results. In the present study I examine the simultaneous projection of population and households in a etropolitan area, under feasibility constraints. A housing-market specification is expressed as a feasibility condition against multipliers of the household composition matrix, extracted here for the Cleveland Consolidated Metropolitan Statistical Area (CMSA), 1990. The feasibility condition is shown to function as a gateway to exogenous considerations regarding the transfer of headship in households, and is exemplified in a forecast of population and households for the Cleveland CMSA.

Household projections are at the centre of the debate about future housing requirements in England. The Census of Population Sample of Anonymised Records offers actual and potential opportunities to ‘add value’ to traditional projections. This article gives examples of such added value, including testing definitional sensitivity of projection outcomes, assisting further detailed disaggregation of projected components, assisting the matching of household projections to dwelling supply, and offering scope to explore via data linkage the relationships between household projections and ‘backlog’ housing needs, affordability, dwelling size, and tenure. The last of these methodologies is examined more closely by using findings from a research project which explored the tenure implications of government household projections on rural areas.

We predict the finite population proportion of a small area when individual-level data are available from a survey and more extensive household-level (not individual-level) data (covariates but not responses) are available from a census. The census and the survey consist of the same strata and primary sampling units (PSU, or wards) that are matched, but the households are not matched. There are some common covariates at the household level in the survey and the census and these covariates are used to link the households within wards. There are also covariates at the ward level, and the wards are the same in the survey and the census. Using a two-stage procedure, we study the multinomial counts in the sampled households within the wards and a projection method to infer about the non-sampled wards. This is accommodated by a multinomial-Dirichlet–Dirichlet model, a three-stage hierarchical Bayesian model for multinomial counts, as it is necessary to account for heterogeneity among the households. The key theoretical contribution of this paper is to develop a computational algorithm to sample the joint posterior density of the multinomial-Dirichlet–Dirichlet model. Specifically, we obtain samples from the distributions of the proportions for each multinomial cell. The second key contribution is to use two projection procedures (parametric based on the nested error regression model and non-parametric based on iterative re-weighted least squares), on these proportions to link the survey to the census, thereby providing a copy of the census counts. We compare the multinomial-Dirichlet–Dirichlet (heterogeneous) model and the multinomial-Dirichlet (homogeneous) model without household effects via these two projection methods. An example of the second Nepal Living Standards Survey is presented.

By using a microsimulation model named INAHSIM, we conducted a household projection in Japan for the period of 2011–2060. Due to rapid aging of the population, the distribution of the elderly (65 years old or older) by living arrangement and dependency level has a profound impact on the future social burden. In this paper, we measured the social burden of the elderly by three variables: (1) institutionalization rate (percentage of the elderly living in institutions), (2) parent-child ratio (relative number of old parents taking into account the number of brothers and sisters), and (3) one-year transition matrix of the elderly by household type. Especially, the choice of the elderly among (a) living independently, (b) coresident with child households, and (c) moving to institutions are crucial indicators for the future social burden of the elderly in Japan.

We argue that the large-dimensional dynamical systems which frequently occur in biological models can sometimes be effectively reduced to much smaller ones. We illustrate this by applying projection operator techniques to a mean-field model of an infectious disease spreading through a population of households. In this way, we are able to accurately approximate the dynamics of the system in terms of a few key quantities greatly reducing the number of equations required. We investigate linear stability in this framework and find a new way of calculating the familiar threshold criterion for household systems.

By using a dynamic micro-simulation model named INAHSIM, we conducted a population-household projection inJapan for the period of 2015 to 2070. Due to rapid aging of the population, the distribution of the elderly (65 yearsold or older) by living arrangements has a profound impact on the social system. Especially, the choice of the elderlyamong a) living in one-person households, b) co-residing with child households, and c) living in institutions, arecrucial indicators for the future social burden of the elderly in Japan. In this paper, we projected the number andproportion of the elderly by living arrangement in future years. Trends of those elderly who have little relatives,therefore having high risk of dying in solitude, were also featured.

The demographic projections have recently become a crucial issue of the demographers’ work, due to the increase of requests, due to the usefulness for the decision-makers and for planning purposes and due to the possibility for them to be used like inputs for other models that study particular aspects related to the population’s structure and to changes in the composition and size of households (pollution, housing, water and food demand…). The knowledge of the future population structure is unavoidable for planning purpose, but is not sufficient. In our society, households constitute a crucial unit of demand for a variety of goods and services, such as housing, transportation and consumption. They represent an essential statistical unit of analysis when dealing with some issues such as the migration projects, the child care and elderly care needs, the per capita greenhouse gas emissions, etc. (Wilson, 2013). In this perspective, both the projected number and the types of household are often required for the purposes of planning and policy making. The aim of this thesis is the review of the forecasting models and a critical analysis of past experiences in order to analyse the international state of the art to define a specific household projection model for Italy.

The thesis handles the topic of families and households from the point of view of EU-SILC, Statistika rodinných účtů and also Sčítání lidu, domů a bytů, especially from the year 2011. It discribes kinds, types of families and households and what is possible on basis of gained information about each family and household see on national as well as international level. Another part of the thesis is focused on definition of poverty limit and it´s impact risks on particular family types mainly in Czech households. On the base of previous development, the future development tendency of number and structure of households and families is mentioned and is expressed by three projections concerning the household development.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003.
Includes bibliographical references (leaves 209-220). Also available in electronic version. Access restricted to campus users.

Die vorliegende Untersuchung widmet sich der Frage, welche Bedeutung die räumliche Differenzierung des Haushaltsbildungsverhaltens für die Ergebnisse von kleinräumigen Haushaltsprognosen hat. Die Haushaltsgrößenstruktur veränderte sich in Deutschland seit ihrer erstmaligen flächendeckenden Erhebung beträchtlich. Diese Strukturveränderungen sind von anhaltenden Haushaltsverkleinerungen geprägt und vollziehen sich auf der Makro-, Meso- und Mikro-ebene in unterschiedlicher Intensität. Eine möglichst exakte Abbildung räumlich differenzierter Trends ist für kleinräumige Haushaltsprognosen ergebnisrelevant. Die Trends ergeben sich zum einen aus der kleinräumigen Bevölkerungsentwicklung und zum anderen aus den Veränderungen des Haushaltsbildungsverhaltens. Um die oben gestellte Frage zu beantworten, wurden zunächst die Veränderungen von Anzahl und Größenstruktur der Haushalte in Deutschland nach dem 2. Weltkrieg nach ihren räumlichen Ausprägungen - zunächst anhand der Literatur und frei zugänglichen Datenquellen - untersucht. Der Fokus der eigenen empirischen Untersuchungen lag auf dem Zeit-raum 1998 bis 2011. Als Hauptdatenquelle wurden Einzeldaten des Mikrozensus im Rahmen von Scientific-Use-Files und der kontrollierten Datenfernverarbeitung genutzt. Um die Bedeutung des Haushaltsbildungsverhaltens beurteilen zu können, musste es operationalisiert werden. Als Grundgerüst diente das Haushaltsvorstandsquotenverfahren, welches jedoch an die Erfordernisse der Untersuchung angepasst werden musste. Aufbauend auf der Operationalisierung wurde mithilfe eines selbst weiterentwickelten Standardisierungsverfahrens der Einfluss des Haushaltsbildungsverhaltens auf die Haushaltsentwicklung bestimmt. Um Aussagen für kleinräumige Entwicklungen treffen zu können, wurden im nächsten Schritt die räumlich und nach Altersgruppen differenzierten Haushaltsvorstands-quoten auf Gemeinden in Sachsen übertragen. Diese Vorgehensweise wird auch in kleinräumigen makroanalytischen Haushaltsprognosen angewendet. Die Berechnungen erfolgten für alle Gemeinden in fünf Varianten und darüber hinaus für ausgewählte Gemeinden des Dresdener Umlandes mit einer Variante auf Basis von kommunalen Daten der Haushaltegenerierung (HHGen). Die Bedeutung der räumlichen Differenzierung ließ sich schließlich durch den Vergleich der Varianten mit der Referenzvariante ohne räumliche Differenzierung sowie dem Vergleich zwischen den vier Varianten der räumlichen Differenzierung messen. Als am besten für die demographisch ausgerichtete Untersuchung geeignet, stellte sich die Definition der Haushaltsbezugsperson nach dem ältesten Haushaltsmitglied heraus. Die anhand des Lebenszykluskonzeptes und altersjahrspezifischer Ausprägungen gewählten acht bzw. sieben Altersgruppen erwiesen sich für räumliche Betrachtungen als günstig und wiesen nur geringe Unterschiede zu altersjahrspezifischen Berechnungen auf. Das Haushaltswachstum in Deutschland betrug im Betrachtungszeitraum 7,7 %. 3,0 % Haushaltswachstum lassen sich auf die Veränderung des Haushaltsbildungsverhaltens zurückführen. Altersstruktureffekte tragen zu einem Wachstum von 5,3 % bei, während dagegen die Veränderung der Bevölkerungszahl bei Ausschluss der anderen Einflussgrößen, zu einem Rückgang von 0,5 % geführt hätte. Die Veränderung des Haushaltsbildungsverhaltens hatte im Betrachtungszeitraum für die Haushaltsentwicklung zweifelsfrei eine hohe Relevanz. Der Einfluss des Haushaltsbildungsverhaltens war im Betrachtungszeitraum für ostdeutsche Bundesländer besonders hoch und in Sachsen mit 8,0 % am höchsten. In Westdeutschland unterschied sich der Einfluss des Haushaltsbildungsverhaltens auf Bundesländerebene deutlich. Darüber hinaus sind insbesondere Stadt-Land-Unterschiede feststellbar. Der Einfluss von stadtregionalen Einflüssen ist aufgrund fehlender Raumkategorien dagegen nicht nachweisbar. Die Erhebungsumstellung des Mikrozensus im Jahr 2005 hat Auswirkungen auf die berechneten Ergebnisse der Haushaltsstruktur und des Haushaltsbildungsverhaltens. Sondereffekte durch die gehäufte Einführung von Zweitwohnsitzsteuern und die sog. Hartz-IV-Reform lassen im Vergleich zu HHGen-Daten Dresdens den Schluss zu, dass es im Zeitraum der Erhebungsumstellung zu einer erhöhten Haushaltsverkleinerung gekommen ist und es sich somit nicht ausschließlich um einen reinen methodischen Effekt handelt. Zu Verzerrungen der regionalen und nach Gemeindetypen differenzierten Ergebnisse können insbesondere Gebietsreformen, Statuswechsel durch dynamische Prozesse sowie Konzeptumstellungen der Typisierungen führen. Am stärksten wirkten sich diese Veränderungen auf den Bevölkerungsmengeneffekt, weniger auf den Verhaltenseffekt aus. Auf Gemeindeebene ergab sich ebenso eine hohe Relevanz des Haushaltsbildungsverhaltens für die Haushaltsentwicklung. Im Maximum führte die räumliche Differenzierung zu einer Abweichung von neun Prozentpunkten im Vergleich zur Referenzvariante. Die Spannweite (R) zwischen den Varianten der räumlichen Differenzierungen ist in Mittelstädten und suburbanen Gemeinden besonders hoch. Für die untersuchten Mittelstädte ist ein Regionaleffekt verantwortlich, d. h. die regionale Differenzierung von Gemeindegrößenklassen führte zu einer Erhöhung der rechnerischen Haushaltsentwicklung. Aus den Ergebnissen lässt sich schlussfolgern, dass von den räumlichen Differenzierungen im Mikrozensus als Ausgangsbasis zunächst Gemeindegrößenklassen am besten geeignet sind. Diese sollten mindestens nach West- und Ostdeutschland unterschieden werden. Die Regionalisierung nach (zusammengefassten) Bundesländern oder zusammengefassten Raumordnungsregionen ist anzustreben, jedoch nur unter großer Sorgfalt umsetzbar, da sonst die Fallzahlen zu gering und der Stichprobenfehler zu hoch werden. Für kleinräumige Haushaltsprognosen ist das Risiko von Fehlprognosen durch die Unterlassung von räumlichen Differenzierungen weitaus höher ist als durch deren Berücksichtigung. Das räumliche Auswertungspotenzial des Mikrozensus ist sehr hoch. Es kann jedoch gegenwärtig nicht voll ausgeschöpft werden. Notwendig wären nachträgliche Gebietsstandsbereinigungen sowie die künftige und rückwirkende Aufnahme geeigneter räumlicher Differenzierungen, die den stadtregionalen Kontext explizit berücksichtigen
The present study addresses the question of the significance of spatial differentiation of household formation behaviour for the results of small-scale household projections. The structure of household sizes in Germany changed significantly since its first nationwide survey. These structural changes are marked by the permanent trend of household size diminishment and take place in varying degrees on macro, meso and micro level. Representing spatially differentiated trends as exactly as possible is of high relevance for the results of small-scale projections of households. These trends result in part from small-scale population development and, secondly, from the changes in household formation behaviour. To answer the question above, the changes in number and size structure of households in Germany after World War II were examined according to their spatial characteristics – as a start in literature and openly accessible data sources. The focus of this thesis’ empirical studies lies on period from 1998 to 2011. The main data source was micro data acquired in the micro-census. These data were used in the context of Scientific Use Files and controlled remote data processing. The assessment of the importance of household formation behaviour requires its operationalization. As backbone the head of household ratio method was used, which, however, had to be adapted to the requirements of the investigation. Based on the operationalization a standardization method developed further in the context of this study was used to determine the influence of household formation behaviour on house-hold development. To be able to draw conclusions for small-scale developments, in a next step head of household ratios differentiated spatially and by age group were applied on municipalities in Saxony – analogous to the approach used in small-scale macro-analytical household projections. The calculations were made for all municipalities for five variants. Furthermore, an additional variant based on local data of household generation (HHGen) was calculated for selected municipalities surrounding Dresden. The importance of spatial differentiation was measured by comparing the variants with a reference calculation without spatial differentiation as well as by comparing between the four variants with spatial differentiation. The definition of the eldest household member as household head proved to be most suitable for demographic studies. Seven respectively eight age groups based on life cycle concept were found to be suitable for spatial considerations and showed only minor differences to year-of-age specific calculations. The number of households increased by 7.7% in the analysis period. 3.0% can be attributed to the change in household formation behaviour. Age structure effects contribute to a growth of 5.3%, whereas the change in population - excluding other influences - would have led to a decline in household numbers of 0.5%. The change in household formation behaviour was doubtless of high relevance in the analysis period. The influence of household formation behaviour in the analysis period was particularly high for East Germany, with the maximum in Saxony (8.0%). In West Germany, the influence of household formation behaviour differed significantly for the different federal states (Länder). Moreover, especially urbanrural differences are noticeable. Urban-suburban interrelations are, however, undetectable due to lack of spatial categories. The change in survey methods for the micro-census in 2005 affects the results of household structure and the calculated household formation behaviour. Compared to HHGen data of Dresden, special effects by the frequent introduction of taxes on secondary residences and the socalled “Hartz IV reform” lead to the conclusion, that an increased household size reduction has taken place in the period of change in survey methods. Consequently, this is not merely a methodological effect. Reforms of regional structures, changes in status caused by dynamic processes as well as changes in concepts of typification may lead to biased regionally differentiated and municipal results. The highest impact of these changes was discovered on population quantity effect, less on the behaviour effect. At municipal level, household formation behaviour showed a high relevance for household development. Spatial differentiation led to a maximal deviation of nine percentage points compared to the reference calculation. The range between the variants of spatial differentiation is particularly high in medium-sized towns and suburban municipalities. For the medium-sized towns this is due to a regional effect: the regional differentiation of municipality size classes led to an increase in the determined household development. The results lead to the conclusion that, choosing from the spatial differentiation possibilities in the micro-census, differentiation on municipality level is most suited as a basis. These should be differentiated at least into West and East Germany. Regionalization to (combined) federal states (Länder) or combined spatial planning regions (Raumordnungsregionen) is desirable. However, it can be implemented only with great care, as there are only a limited number of cases and the sampling error would be too high. For small-scale household projections the risk of incorrect predictions by the omission of spatial differentiation is is much higher than by taking them into account. The potential of spatial analysis of the micro-census is very high, but cannot be exploited to the fullest at the time being. Subsequent territorial adjustments would be necessary, as well as future and retroactive inclusion of appropriate spatial differentiations which explicitly take into account the intraregional context

碩士
南華大學
社會學研究所
94
Assertions of extended family was popular before modern society and modernization caused the transition of family structure were visible in literature. However, positive studies indicated that no matter in western or eastern society, household size normally was less than six because of economic difficulty, psychological conflict and survival constraint, therefore, stem family was an upper limit of family growth. Specifically speaking, factors affecting family structure can be categorized to willingness and availability of intergenerational co-residence, and the willingness works only within the constraint of availability. Availability depends on fertility, mortality and migration, while willingness on propensity of leaving parental home. In Taiwan unmarried birth-giving is discouraged so that marriage is also an important factor affecting the trend of family change. Using a multi-dimensional household projection model developed by Zeng et al., this paper projects the number and composition of family households in Taiwan up to the year 2050 to explore the impacts of population change and propensity of intergenerational co-residence on the change of household composition. 　 　　Three categories of data -- base population, standard schedules and summary measures are required. We use 1990 census but not 2000 census as the base population for two reasons. Firstly, there is a shortage of 290,033 persons comparing with registered population in 2000 while the shortage in 1990 is only 79,976. Secondly, we can make a comparison between the results of projection and registration/census in 2000 to evaluate the accuracy of this model. Standard schedules define the stable age pattern of vital rates. They will be combined to variable summary measures in order to capture the sex-age-specific vital rates in the future. We derived sex-age specific vital rates including mortality, fertility, nuptiality, international migration and living parental home from recent survey or registered data to make standard schedules and set three scenarios for summary measures including life expectancy at birth, total fertility rate by marital status and parity, probability of ever marrying, probability of a marriage end in divorce, probability of remarriage from divorce and widowed, mean age at first marriage, propensity of living parental home, and number of emigrant and immigrant. 　 　　Results firstly show the population differences between projection and registration on sex-age-specific number of persons and the household differences between projection and census for the year 2000. In sex-age-specific number of persons, due to the original deficit of military forces in the 1990 base population, we get the largest deviation on age group 34-44 which accounts 1.7％ of registered persons. Nevertheless, there is only one percent of deviation in overall. In household composition, our projection may be more reliable than census because there is an unreasonable proportion of one person household -- 21.52％ in census 2000 while it is only 13.44％ in 1990 census and our result is 13.85％. We suspect it is resulted from the extension of a special data collecting method -- official informing system. 　 　　There are three scenarios of household projections to demonstrate the trend of population and household change. The middle projection generally owns all summary measure in the current level. For example, the TFR will go on decreasing, then fixed at 1.10 from 2010 to 2050. The high projection owns the highest fertility rates, propensity of marrying, and lowest probability of leaving parental home. The low projection owns the lowest fertility rates, propensity of marrying, and highest probability of leaving parental home. Under the middle projection, the proportion of 65 years old and above is 15.22％ and the proportion of 14 years old and below is 12.75％ in 2020, corresponding to a dependent ratio of 38.83％, and the dependent ratio will rise to 74.14％ in 2050. Under the low projection with TFR decreasing to 0.8 on 2010 and after, the proportion of 65 years old and above is 37.97％. If the TFR begins to go up to the replacement level in 2010, then the proportion of 65 years old and above is 26.58％. 　 　　About changes in the household composition, it''s found that due to the under- replacement fertility since the early 1980s, single generation households will be dramatically increasing on and after 2020 while the increase of elderly households contribute substantially to the growth of this category. In 2050, more than 15% of the elderly will be living alone under moderate assumptions. This entails some grave conditions for the implementation and operation of national pension program, and the long-term care programs. In another hand, single-parent household will be much more prevalent because of the growing divorce rate, especially for divorced women since the probability of remarriage from divorce for female is lower than their male counterpart.

Die vorliegende Untersuchung widmet sich der Frage, welche Bedeutung die räumliche Differenzierung des Haushaltsbildungsverhaltens für die Ergebnisse von kleinräumigen Haushaltsprognosen hat. Die Haushaltsgrößenstruktur veränderte sich in Deutschland seit ihrer erstmaligen flächendeckenden Erhebung beträchtlich. Diese Strukturveränderungen sind von anhaltenden Haushaltsverkleinerungen geprägt und vollziehen sich auf der Makro-, Meso- und Mikro-ebene in unterschiedlicher Intensität. Eine möglichst exakte Abbildung räumlich differenzierter Trends ist für kleinräumige Haushaltsprognosen ergebnisrelevant. Die Trends ergeben sich zum einen aus der kleinräumigen Bevölkerungsentwicklung und zum anderen aus den Veränderungen des Haushaltsbildungsverhaltens. Um die oben gestellte Frage zu beantworten, wurden zunächst die Veränderungen von Anzahl und Größenstruktur der Haushalte in Deutschland nach dem 2. Weltkrieg nach ihren räumlichen Ausprägungen - zunächst anhand der Literatur und frei zugänglichen Datenquellen - untersucht. Der Fokus der eigenen empirischen Untersuchungen lag auf dem Zeit-raum 1998 bis 2011. Als Hauptdatenquelle wurden Einzeldaten des Mikrozensus im Rahmen von Scientific-Use-Files und der kontrollierten Datenfernverarbeitung genutzt. Um die Bedeutung des Haushaltsbildungsverhaltens beurteilen zu können, musste es operationalisiert werden. Als Grundgerüst diente das Haushaltsvorstandsquotenverfahren, welches jedoch an die Erfordernisse der Untersuchung angepasst werden musste. Aufbauend auf der Operationalisierung wurde mithilfe eines selbst weiterentwickelten Standardisierungsverfahrens der Einfluss des Haushaltsbildungsverhaltens auf die Haushaltsentwicklung bestimmt. Um Aussagen für kleinräumige Entwicklungen treffen zu können, wurden im nächsten Schritt die räumlich und nach Altersgruppen differenzierten Haushaltsvorstands-quoten auf Gemeinden in Sachsen übertragen. Diese Vorgehensweise wird auch in kleinräumigen makroanalytischen Haushaltsprognosen angewendet. Die Berechnungen erfolgten für alle Gemeinden in fünf Varianten und darüber hinaus für ausgewählte Gemeinden des Dresdener Umlandes mit einer Variante auf Basis von kommunalen Daten der Haushaltegenerierung (HHGen). Die Bedeutung der räumlichen Differenzierung ließ sich schließlich durch den Vergleich der Varianten mit der Referenzvariante ohne räumliche Differenzierung sowie dem Vergleich zwischen den vier Varianten der räumlichen Differenzierung messen. Als am besten für die demographisch ausgerichtete Untersuchung geeignet, stellte sich die Definition der Haushaltsbezugsperson nach dem ältesten Haushaltsmitglied heraus. Die anhand des Lebenszykluskonzeptes und altersjahrspezifischer Ausprägungen gewählten acht bzw. sieben Altersgruppen erwiesen sich für räumliche Betrachtungen als günstig und wiesen nur geringe Unterschiede zu altersjahrspezifischen Berechnungen auf. Das Haushaltswachstum in Deutschland betrug im Betrachtungszeitraum 7,7 %. 3,0 % Haushaltswachstum lassen sich auf die Veränderung des Haushaltsbildungsverhaltens zurückführen. Altersstruktureffekte tragen zu einem Wachstum von 5,3 % bei, während dagegen die Veränderung der Bevölkerungszahl bei Ausschluss der anderen Einflussgrößen, zu einem Rückgang von 0,5 % geführt hätte. Die Veränderung des Haushaltsbildungsverhaltens hatte im Betrachtungszeitraum für die Haushaltsentwicklung zweifelsfrei eine hohe Relevanz. Der Einfluss des Haushaltsbildungsverhaltens war im Betrachtungszeitraum für ostdeutsche Bundesländer besonders hoch und in Sachsen mit 8,0 % am höchsten. In Westdeutschland unterschied sich der Einfluss des Haushaltsbildungsverhaltens auf Bundesländerebene deutlich. Darüber hinaus sind insbesondere Stadt-Land-Unterschiede feststellbar. Der Einfluss von stadtregionalen Einflüssen ist aufgrund fehlender Raumkategorien dagegen nicht nachweisbar. Die Erhebungsumstellung des Mikrozensus im Jahr 2005 hat Auswirkungen auf die berechneten Ergebnisse der Haushaltsstruktur und des Haushaltsbildungsverhaltens. Sondereffekte durch die gehäufte Einführung von Zweitwohnsitzsteuern und die sog. Hartz-IV-Reform lassen im Vergleich zu HHGen-Daten Dresdens den Schluss zu, dass es im Zeitraum der Erhebungsumstellung zu einer erhöhten Haushaltsverkleinerung gekommen ist und es sich somit nicht ausschließlich um einen reinen methodischen Effekt handelt. Zu Verzerrungen der regionalen und nach Gemeindetypen differenzierten Ergebnisse können insbesondere Gebietsreformen, Statuswechsel durch dynamische Prozesse sowie Konzeptumstellungen der Typisierungen führen. Am stärksten wirkten sich diese Veränderungen auf den Bevölkerungsmengeneffekt, weniger auf den Verhaltenseffekt aus. Auf Gemeindeebene ergab sich ebenso eine hohe Relevanz des Haushaltsbildungsverhaltens für die Haushaltsentwicklung. Im Maximum führte die räumliche Differenzierung zu einer Abweichung von neun Prozentpunkten im Vergleich zur Referenzvariante. Die Spannweite (R) zwischen den Varianten der räumlichen Differenzierungen ist in Mittelstädten und suburbanen Gemeinden besonders hoch. Für die untersuchten Mittelstädte ist ein Regionaleffekt verantwortlich, d. h. die regionale Differenzierung von Gemeindegrößenklassen führte zu einer Erhöhung der rechnerischen Haushaltsentwicklung. Aus den Ergebnissen lässt sich schlussfolgern, dass von den räumlichen Differenzierungen im Mikrozensus als Ausgangsbasis zunächst Gemeindegrößenklassen am besten geeignet sind. Diese sollten mindestens nach West- und Ostdeutschland unterschieden werden. Die Regionalisierung nach (zusammengefassten) Bundesländern oder zusammengefassten Raumordnungsregionen ist anzustreben, jedoch nur unter großer Sorgfalt umsetzbar, da sonst die Fallzahlen zu gering und der Stichprobenfehler zu hoch werden. Für kleinräumige Haushaltsprognosen ist das Risiko von Fehlprognosen durch die Unterlassung von räumlichen Differenzierungen weitaus höher ist als durch deren Berücksichtigung. Das räumliche Auswertungspotenzial des Mikrozensus ist sehr hoch. Es kann jedoch gegenwärtig nicht voll ausgeschöpft werden. Notwendig wären nachträgliche Gebietsstandsbereinigungen sowie die künftige und rückwirkende Aufnahme geeigneter räumlicher Differenzierungen, die den stadtregionalen Kontext explizit berücksichtigen.:INHALTSVERZEICHNIS ABBILDUNGSVERZEICHNIS TABELLENVERZEICHNIS ABKÜRZUNGSVERZEICHNIS KURZFASSUNG ABSTRACT 1. EINFÜHRUNG 21 1.1 PROBLEMSTELLUNG 21 1.2 ZIEL UND AUFBAU DER ARBEIT 26 2. GRUNDZÜGE EINER BEVÖLKERUNGSGEOGRAPHISCH AUSGERICHTETEN HAUSHALTSFORSCHUNG 29 2.1 EMPIRISCHE HAUSHALTSFORSCHUNG IM BEVÖLKERUNGSGEOGRAPHISCHEN KONTEXT 29 2.2 ZUSAMMENHÄNGE ZWISCHEN BEVÖLKERUNGS- UND HAUSHALTSENTWICKLUNG 32 2.3 ZENTRALE BEGRIFFE 36 2.3.1 Privater Haushalt 37 2.3.1.1 Herkunft und Bedeutung 37 2.3.1.2 Abgrenzung zu anderen Formen des Zusammenlebens 38 2.3.2 Haushaltsbildungsverhalten 40 2.3.3 Räumliche Differenzierung 43 3. GRUNDLAGEN DER ERKLÄRUNG, ANALYSE UND PROGNOSE VON RÄUMLICH UNTERSCHIEDLICH VERLAUFENDEN DYNAMIKEN DER ANZAHL UND STRUKTUR PRIVATER HAUSHALTE 44 3.1 DAS LEBENSZYKLUSKONZEPT ALS GRUNDSÄTZLICHES ERKLÄRUNGSMODELL DES INDIVIDUELLEN HAUSHALTSBILDUNGS- UND AUFLÖSUNGSPROZESSES 44 3.2 THEORIEANSÄTZE ZUR ERKLÄRUNG DES SICH VERÄNDERNDEN HAUSHALTSBILDUNGSVERHALTENS 49 3.2.1 Demographische Theorieansätze 49 3.2.2 Soziologische Theorieansätze 56 3.2.2.1 Individualisierungsthese 57 3.2.2.2 Theorie gesellschaftlicher/sozialer Differenzierung privater Lebensformen 59 3.2.3 Zwischenfazit 61 3.3 DYNAMIK DER HAUSHALTSGRÖßENSTRUKTUR IN DEUTSCHLAND 64 3.3.1 Vorbemerkung 64 3.3.2 Haushaltsgrößenveränderungen im Überblick 64 3.3.2.1 Historische Entwicklung 64 3.3.2.2 Internationaler Vergleich 72 3.3.3 Veränderung von Haushaltsgrößenstrukturen und Haushaltsbildungsverhalten in Deutschland 75 3.3.3.1 Quellen- und Literaturüberblick 75 3.3.3.2 Überregionale Entwicklungen und Zusammenhänge 77 3.3.3.3 Ausgewählte Erkenntnisse regionaler Betrachtungen 88 3.3.3.4 Ausgewählte Erkenntnisse intraregionaler und innerstädtischer Betrachtungen 95 3.3.4 Zwischenfazit 105 3.4 DATENGRUNDLAGEN FÜR ANALYSEN DES HAUSHALTSBILDUNGSVERHALTENS IN DEUTSCHLAND 107 3.4.1 Anforderungen an Datengrundlagen für kleinräumige und regionale Betrachtungen 107 3.4.2 Überblick zu für Forschungszwecke nutzbaren Datenquellen 107 3.4.3 Kommunales Haushaltegenerierungsverfahren HHGen 110 3.4.4 Sozio-oekonomisches Panel (SOEP) 111 3.4.5 Zensus 2011 112 3.4.6 Mikrozensus 113 3.4.6.1 Datenerhebungsverfahren und daraus resultierende Konsequenzen 113 3.4.6.2 Möglichkeiten und Grenzen der räumlichen Differenzierung 116 3.4.7 Zwischenfazit 120 3.5 AUSGEWÄHLTE HAUSHALTSPROGNOSEVERFAHREN UND IHRE DATENANFORDERUNGEN 123 3.5.1 Überblick 123 3.5.2 Makroanalytische Verfahren 125 3.5.2.1 Haushaltsmitgliederquotenverfahren 126 3.5.2.2 Haushaltsvorstandsquotenverfahren 127 3.5.2.3 Die IÖR-Haushaltsprognose - ein Beispiel für die Weiterentwicklung makroanalytischer Verfahren für kleinräumige Anwendungen 130 3.6 SCHLUSSFOLGERUNGEN FÜR DIE EMPIRISCHE ARBEIT 132 4. OPERATIONALISIERUNG DER VERÄNDERUNG DES HAUSHALTSBILDUNGSVERHALTENS BEI MÖGLICHST HOHER RÄUMLICHER DIFFERENZIERUNG 133 4.1 VORBEMERKUNGEN 133 4.2 BESONDERHEITEN DER MESSUNG VON HAUSHALTSGRÖßENSTRUKTUREN 135 4.3 DEFINITION DER HAUSHALTSBEZUGSPERSON – EIN VERGLEICH 138 4.3.1 Bestehende Konzepte 138 4.3.2 Empirischer Vergleich der Definitionen der Haushaltsbezugsperson 141 4.3.2.1 Vergleich insgesamt 141 4.3.2.2 Vergleich nach Geschlecht 149 4.3.3 Zwischenfazit 155 4.4 DIFFERENZIERUNG NACH ALTER UND BILDUNG VON ALTERSGRUPPEN 157 4.5 FESTLEGUNGEN ZUR OPERATIONALISIERUNG DES HAUSHALTSBILDUNGS-VERHALTENS IM ÜBERBLICK 165 4.6 METHODIK ZUR ERMITTLUNG VON EINFLUSSGRÖßEN DER HAUSHALTSENTWICKLUNG 166 4.7 METHODISCHE VORGEHENSWEISE EX-POST-PROGNOSEN 172 5. ERGEBNISSE EMPIRISCHER ANALYSEN ZUR RÄUMLICHEN DIFFERENZIERUNG DER VERÄNDERUNG DES HAUSHALTSBILDUNGSVERHALTENS IN DEUTSCHLAND 176 5.1 VORBEMERKUNGEN 176 5.2 HAUSHALTSGRÖßENENTWICKLUNG UND EINFLUSSGRÖßEN DER HAUSHALTSENTWICKLUNG 177 5.2.1 Vorgehensweise 177 5.2.2 Regionale Differenzierung 177 5.2.2.1 Bundesländer sowie West- und Ostdeutschland 177 5.2.2.2 Raumordnungsregionen 194 5.2.3 Gemeindetypen 207 5.2.3.1 Stadt-Land-Gliederung Eurostat bis 2011 208 5.2.3.2 Siedlungsstrukturelle Gemeindetypen 217 5.2.3.3 Gemeindegrößenklassen 225 5.2.3.4 Zusammengefasste Gemeindegrößenklassen nach zusammengefassten Raumordnungsregionen 235 5.2.3.5 Weitere Möglichkeiten der räumlichen Differenzierung im Mikrozensus 239 5.2.4 Analysen mit HHGen-Daten der Landeshauptstadt Dresden 240 5.2.5 Zwischenfazit 248 5.3 WIRKUNG DER RÄUMLICHEN DIFFERENZIERUNG DES HAUSHALTSBILDUNGSVERHALTENS AUF GEMEINDEEBENE AM BEISPIEL VON SACHSEN 253 5.3.1 Vorbemerkungen 253 5.3.2 Bevölkerungsentwicklung auf Gemeindeebene sowie Variante ohne räumliche Differenzierung als Vergleichsbasis 254 5.3.3 Gemeindegrößenklassen Ostdeutschland 258 5.3.4 Testrechnung für angrenzende Dresdener Umlandgemeinden anhand von HHGen-Daten 264 5.3.5 Varianten der räumlichen Differenzierung im Vergleich 267 5.3.5.1 Gesamtentwicklung nach ausgewählten Kategorien 267 5.3.5.2 Einzelfallbetrachtung ausgewählter Gemeinden 274 5.3.6 Zwischenfazit 281 6. SCHLUSSFOLGERUNGEN UND AUSBLICK 286 6.1 SCHLUSSFOLGERUNGEN FÜR DIE RÄUMLICHE DIFFERENZIERUNG DES HAUSHALTSBILDUNGSVERHALTENS ALS GRUNDLAGE KLEINRÄUMIGER HAUSHALTSPROGNOSEN 286 6.2 AUSBLICK 297 LITERATURVERZEICHNIS 299 WEITERE QUELLEN 317 ANHANG
The present study addresses the question of the significance of spatial differentiation of household formation behaviour for the results of small-scale household projections. The structure of household sizes in Germany changed significantly since its first nationwide survey. These structural changes are marked by the permanent trend of household size diminishment and take place in varying degrees on macro, meso and micro level. Representing spatially differentiated trends as exactly as possible is of high relevance for the results of small-scale projections of households. These trends result in part from small-scale population development and, secondly, from the changes in household formation behaviour. To answer the question above, the changes in number and size structure of households in Germany after World War II were examined according to their spatial characteristics – as a start in literature and openly accessible data sources. The focus of this thesis’ empirical studies lies on period from 1998 to 2011. The main data source was micro data acquired in the micro-census. These data were used in the context of Scientific Use Files and controlled remote data processing. The assessment of the importance of household formation behaviour requires its operationalization. As backbone the head of household ratio method was used, which, however, had to be adapted to the requirements of the investigation. Based on the operationalization a standardization method developed further in the context of this study was used to determine the influence of household formation behaviour on house-hold development. To be able to draw conclusions for small-scale developments, in a next step head of household ratios differentiated spatially and by age group were applied on municipalities in Saxony – analogous to the approach used in small-scale macro-analytical household projections. The calculations were made for all municipalities for five variants. Furthermore, an additional variant based on local data of household generation (HHGen) was calculated for selected municipalities surrounding Dresden. The importance of spatial differentiation was measured by comparing the variants with a reference calculation without spatial differentiation as well as by comparing between the four variants with spatial differentiation. The definition of the eldest household member as household head proved to be most suitable for demographic studies. Seven respectively eight age groups based on life cycle concept were found to be suitable for spatial considerations and showed only minor differences to year-of-age specific calculations. The number of households increased by 7.7% in the analysis period. 3.0% can be attributed to the change in household formation behaviour. Age structure effects contribute to a growth of 5.3%, whereas the change in population - excluding other influences - would have led to a decline in household numbers of 0.5%. The change in household formation behaviour was doubtless of high relevance in the analysis period. The influence of household formation behaviour in the analysis period was particularly high for East Germany, with the maximum in Saxony (8.0%). In West Germany, the influence of household formation behaviour differed significantly for the different federal states (Länder). Moreover, especially urbanrural differences are noticeable. Urban-suburban interrelations are, however, undetectable due to lack of spatial categories. The change in survey methods for the micro-census in 2005 affects the results of household structure and the calculated household formation behaviour. Compared to HHGen data of Dresden, special effects by the frequent introduction of taxes on secondary residences and the socalled “Hartz IV reform” lead to the conclusion, that an increased household size reduction has taken place in the period of change in survey methods. Consequently, this is not merely a methodological effect. Reforms of regional structures, changes in status caused by dynamic processes as well as changes in concepts of typification may lead to biased regionally differentiated and municipal results. The highest impact of these changes was discovered on population quantity effect, less on the behaviour effect. At municipal level, household formation behaviour showed a high relevance for household development. Spatial differentiation led to a maximal deviation of nine percentage points compared to the reference calculation. The range between the variants of spatial differentiation is particularly high in medium-sized towns and suburban municipalities. For the medium-sized towns this is due to a regional effect: the regional differentiation of municipality size classes led to an increase in the determined household development. The results lead to the conclusion that, choosing from the spatial differentiation possibilities in the micro-census, differentiation on municipality level is most suited as a basis. These should be differentiated at least into West and East Germany. Regionalization to (combined) federal states (Länder) or combined spatial planning regions (Raumordnungsregionen) is desirable. However, it can be implemented only with great care, as there are only a limited number of cases and the sampling error would be too high. For small-scale household projections the risk of incorrect predictions by the omission of spatial differentiation is is much higher than by taking them into account. The potential of spatial analysis of the micro-census is very high, but cannot be exploited to the fullest at the time being. Subsequent territorial adjustments would be necessary, as well as future and retroactive inclusion of appropriate spatial differentiations which explicitly take into account the intraregional context.:INHALTSVERZEICHNIS ABBILDUNGSVERZEICHNIS TABELLENVERZEICHNIS ABKÜRZUNGSVERZEICHNIS KURZFASSUNG ABSTRACT 1. EINFÜHRUNG 21 1.1 PROBLEMSTELLUNG 21 1.2 ZIEL UND AUFBAU DER ARBEIT 26 2. GRUNDZÜGE EINER BEVÖLKERUNGSGEOGRAPHISCH AUSGERICHTETEN HAUSHALTSFORSCHUNG 29 2.1 EMPIRISCHE HAUSHALTSFORSCHUNG IM BEVÖLKERUNGSGEOGRAPHISCHEN KONTEXT 29 2.2 ZUSAMMENHÄNGE ZWISCHEN BEVÖLKERUNGS- UND HAUSHALTSENTWICKLUNG 32 2.3 ZENTRALE BEGRIFFE 36 2.3.1 Privater Haushalt 37 2.3.1.1 Herkunft und Bedeutung 37 2.3.1.2 Abgrenzung zu anderen Formen des Zusammenlebens 38 2.3.2 Haushaltsbildungsverhalten 40 2.3.3 Räumliche Differenzierung 43 3. GRUNDLAGEN DER ERKLÄRUNG, ANALYSE UND PROGNOSE VON RÄUMLICH UNTERSCHIEDLICH VERLAUFENDEN DYNAMIKEN DER ANZAHL UND STRUKTUR PRIVATER HAUSHALTE 44 3.1 DAS LEBENSZYKLUSKONZEPT ALS GRUNDSÄTZLICHES ERKLÄRUNGSMODELL DES INDIVIDUELLEN HAUSHALTSBILDUNGS- UND AUFLÖSUNGSPROZESSES 44 3.2 THEORIEANSÄTZE ZUR ERKLÄRUNG DES SICH VERÄNDERNDEN HAUSHALTSBILDUNGSVERHALTENS 49 3.2.1 Demographische Theorieansätze 49 3.2.2 Soziologische Theorieansätze 56 3.2.2.1 Individualisierungsthese 57 3.2.2.2 Theorie gesellschaftlicher/sozialer Differenzierung privater Lebensformen 59 3.2.3 Zwischenfazit 61 3.3 DYNAMIK DER HAUSHALTSGRÖßENSTRUKTUR IN DEUTSCHLAND 64 3.3.1 Vorbemerkung 64 3.3.2 Haushaltsgrößenveränderungen im Überblick 64 3.3.2.1 Historische Entwicklung 64 3.3.2.2 Internationaler Vergleich 72 3.3.3 Veränderung von Haushaltsgrößenstrukturen und Haushaltsbildungsverhalten in Deutschland 75 3.3.3.1 Quellen- und Literaturüberblick 75 3.3.3.2 Überregionale Entwicklungen und Zusammenhänge 77 3.3.3.3 Ausgewählte Erkenntnisse regionaler Betrachtungen 88 3.3.3.4 Ausgewählte Erkenntnisse intraregionaler und innerstädtischer Betrachtungen 95 3.3.4 Zwischenfazit 105 3.4 DATENGRUNDLAGEN FÜR ANALYSEN DES HAUSHALTSBILDUNGSVERHALTENS IN DEUTSCHLAND 107 3.4.1 Anforderungen an Datengrundlagen für kleinräumige und regionale Betrachtungen 107 3.4.2 Überblick zu für Forschungszwecke nutzbaren Datenquellen 107 3.4.3 Kommunales Haushaltegenerierungsverfahren HHGen 110 3.4.4 Sozio-oekonomisches Panel (SOEP) 111 3.4.5 Zensus 2011 112 3.4.6 Mikrozensus 113 3.4.6.1 Datenerhebungsverfahren und daraus resultierende Konsequenzen 113 3.4.6.2 Möglichkeiten und Grenzen der räumlichen Differenzierung 116 3.4.7 Zwischenfazit 120 3.5 AUSGEWÄHLTE HAUSHALTSPROGNOSEVERFAHREN UND IHRE DATENANFORDERUNGEN 123 3.5.1 Überblick 123 3.5.2 Makroanalytische Verfahren 125 3.5.2.1 Haushaltsmitgliederquotenverfahren 126 3.5.2.2 Haushaltsvorstandsquotenverfahren 127 3.5.2.3 Die IÖR-Haushaltsprognose - ein Beispiel für die Weiterentwicklung makroanalytischer Verfahren für kleinräumige Anwendungen 130 3.6 SCHLUSSFOLGERUNGEN FÜR DIE EMPIRISCHE ARBEIT 132 4. OPERATIONALISIERUNG DER VERÄNDERUNG DES HAUSHALTSBILDUNGSVERHALTENS BEI MÖGLICHST HOHER RÄUMLICHER DIFFERENZIERUNG 133 4.1 VORBEMERKUNGEN 133 4.2 BESONDERHEITEN DER MESSUNG VON HAUSHALTSGRÖßENSTRUKTUREN 135 4.3 DEFINITION DER HAUSHALTSBEZUGSPERSON – EIN VERGLEICH 138 4.3.1 Bestehende Konzepte 138 4.3.2 Empirischer Vergleich der Definitionen der Haushaltsbezugsperson 141 4.3.2.1 Vergleich insgesamt 141 4.3.2.2 Vergleich nach Geschlecht 149 4.3.3 Zwischenfazit 155 4.4 DIFFERENZIERUNG NACH ALTER UND BILDUNG VON ALTERSGRUPPEN 157 4.5 FESTLEGUNGEN ZUR OPERATIONALISIERUNG DES HAUSHALTSBILDUNGS-VERHALTENS IM ÜBERBLICK 165 4.6 METHODIK ZUR ERMITTLUNG VON EINFLUSSGRÖßEN DER HAUSHALTSENTWICKLUNG 166 4.7 METHODISCHE VORGEHENSWEISE EX-POST-PROGNOSEN 172 5. ERGEBNISSE EMPIRISCHER ANALYSEN ZUR RÄUMLICHEN DIFFERENZIERUNG DER VERÄNDERUNG DES HAUSHALTSBILDUNGSVERHALTENS IN DEUTSCHLAND 176 5.1 VORBEMERKUNGEN 176 5.2 HAUSHALTSGRÖßENENTWICKLUNG UND EINFLUSSGRÖßEN DER HAUSHALTSENTWICKLUNG 177 5.2.1 Vorgehensweise 177 5.2.2 Regionale Differenzierung 177 5.2.2.1 Bundesländer sowie West- und Ostdeutschland 177 5.2.2.2 Raumordnungsregionen 194 5.2.3 Gemeindetypen 207 5.2.3.1 Stadt-Land-Gliederung Eurostat bis 2011 208 5.2.3.2 Siedlungsstrukturelle Gemeindetypen 217 5.2.3.3 Gemeindegrößenklassen 225 5.2.3.4 Zusammengefasste Gemeindegrößenklassen nach zusammengefassten Raumordnungsregionen 235 5.2.3.5 Weitere Möglichkeiten der räumlichen Differenzierung im Mikrozensus 239 5.2.4 Analysen mit HHGen-Daten der Landeshauptstadt Dresden 240 5.2.5 Zwischenfazit 248 5.3 WIRKUNG DER RÄUMLICHEN DIFFERENZIERUNG DES HAUSHALTSBILDUNGSVERHALTENS AUF GEMEINDEEBENE AM BEISPIEL VON SACHSEN 253 5.3.1 Vorbemerkungen 253 5.3.2 Bevölkerungsentwicklung auf Gemeindeebene sowie Variante ohne räumliche Differenzierung als Vergleichsbasis 254 5.3.3 Gemeindegrößenklassen Ostdeutschland 258 5.3.4 Testrechnung für angrenzende Dresdener Umlandgemeinden anhand von HHGen-Daten 264 5.3.5 Varianten der räumlichen Differenzierung im Vergleich 267 5.3.5.1 Gesamtentwicklung nach ausgewählten Kategorien 267 5.3.5.2 Einzelfallbetrachtung ausgewählter Gemeinden 274 5.3.6 Zwischenfazit 281 6. SCHLUSSFOLGERUNGEN UND AUSBLICK 286 6.1 SCHLUSSFOLGERUNGEN FÜR DIE RÄUMLICHE DIFFERENZIERUNG DES HAUSHALTSBILDUNGSVERHALTENS ALS GRUNDLAGE KLEINRÄUMIGER HAUSHALTSPROGNOSEN 286 6.2 AUSBLICK 297 LITERATURVERZEICHNIS 299 WEITERE QUELLEN 317 ANHANG

Families and households in census data with a focus on the methodological aspects of the data Abstract Over the past few decades, significant changes in the family and household structure have been observed. Nevertheless, demographic behaviour does not have to be the only factor affecting these changes. Therefore, the thesis brings a comprehensive look at the family and household and focuses more on the methodological aspects of its structure and development evaluation. The first part of the thesis is rather a methodological work and introduces a detailed household methodology of one of the most important data source on families and households. Over the last half- century, the population and housing census has allowed a monitoring of household formation in the Czech Republic. Despite the efforts, new technologies, data collection and processing methods have required a change of the household concept in the last census. Since then, the time series have not been fully comparable. For the first time, household type derivation was based on automated process only, using a predefined algorithm. This algorithm, drafted by the author of the thesis, is also introduced in a separate chapter. The thesis also includes analytical chapters discussing the long-term development of the family and household structure...

Waste management is among the priority areas in the policy of Bulgaria, as part of the EU. Improving the environment by reducing landfilled waste, achieving balance and sustainability in different regions of our country, priority orientation to products from biodegradable household waste, effective reduction of greenhouse gas emissions, improving the condition of soils in Bulgaria, and preserving natural diversity are among the key objectives. Bulgaria's developed National Waste Plan until 2028 is a serious query to find ways to solve the problem of garbage in the country and create conditions for a successful transition to a circular economy. The purpose of the report is to analyze the costs of waste management in Bulgaria for the period 2015-2020 and to characterize the National Plan for Waste Management in Bulgaria until 2028.

Palm Beach County (Florida) Solid Waste Authority built an integrated solid waste management system in the 1980s and 1990s around an 1,800 tpd Refuse Derived Fuel (RDF) Waste-to-Energy (WTE) facility. The system included a network of five regional transfer stations, Subtitle D sanitary landfill, recovered materials processing facility, composting facility, metals processing facility and household hazardous waste collection program. The WTE, which became operational in 1989, was built with two 900 tpd RDF combustion units. Space was provided for the addition of a third combustion unit, a second turbine-generator and an extra flue was installed in the facility’s stack. By 2004, the WTE was fifteen years old. It had been running at over 125% availability and well above its nominal capacity for almost a decade. Landfill capacity was being consumed at a rate which would see it filled in less than 20 years. The County had been hit with repeated hurricanes in recent years and the County’s population was continuing to grow making landfill capacity projections far from certain. The Authority began an assessment of its long term capacity options which included renovation of its existing WTE facility, expansion of that facility, development of a new WTE facility, development of a new Subtitle D Landfill and several out-of-county options. This paper will focus on the results of this assessment with emphasis on the current efforts to develop a new Mass Burn WTE facility with a capacity of 3,000 tpd and a commercial operations date of 2015. It will be the largest new WTE built in North America in more than 20 years. The choice of Mass Burn technology, facility and combustion module sizing, air pollution control technology, facility site selection, environmental permitting, public outreach program, project financing and procurement and contracting approach will be discussed.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

According to future projections based on current demographic growth trends, Auckland’s population will reach two million in 2033. Since the city is already afflicted by a serious housing crisis, at the beginning of 2017 the newly elected Mayor Phil Goff set up a task force. Formed by representatives of various stakeholders, it was given the task of producing a report with strategic and tactical guidelines to mitigate the situation. Unitec researchers were invited to respond to the report, which came out at the end of 2017, in the form of three think pieces towards the Building Better Homes, Towns and Cities National Science Challenge. This paper is a new iteration of one of these think pieces, focused on collaborative living, and expands on the new role that designers should play in this field. Its ideological position is that the house cannot and should not be considered as a commodity on the free market; nor should focus solely be on bringing down prices by increasing the number of houses on offer. Over time, housing might evolve to being more about social (use) value than exchange value. Other models of the production and consumption of household goods are documented throughout the world as alternatives to mainstream market logic, using collective procurement mechanisms to cut construction and marketing costs with savings of up to 30%. These experiments, not limited to achieving financially sustainable outcomes, are linked to new social practices of collaboration between neighbours. The sharing of spaces and equipment to complement private housing units also leads to social and environmental sustainability.

In the second quarter, annual inflation (9.67%), the technical staff’s projections and its expectations continued to increase, remaining above the target. International cost shocks, accentuated by Russia's invasion of Ukraine, have been more persistent than projected, thus contributing to higher inflation. The effects of indexation, higher than estimated excess demand, a tighter labor market, inflation expectations that continue to rise and currently exceed 3%, and the exchange rate pressures add to those described above. High core inflation measures as well as in the producer price index (PPI) across all baskets confirm a significant spread in price increases. Compared to estimates presented in April, the new forecast trajectory for headline and core inflation increased. This was partly the result of greater exchange rate pressure on prices, and a larger output gap, which is expected to remain positive for the remainder of 2022 and which is estimated to close towards yearend 2023. In addition, these trends take into account higher inflation rate indexation, more persistent above-target inflation expectations, a quickening of domestic fuel price increases due to the correction of lags versus the parity price and higher international oil price forecasts. The forecast supposes a good domestic supply of perishable foods, although it also considers that international prices of processed foods will remain high. In terms of the goods sub-basket, the end of the national health emergency implies a reversal of the value-added tax (VAT) refund applied to health and personal hygiene products, resulting in increases in the prices of these goods. Alternatively, the monetary policy adjustment process and the moderation of external shocks would help inflation and its expectations to begin to decrease over time and resume their alignment with the target. Thus, the new projection suggests that inflation could remain high for the second half of 2022, closing at 9.7%. However, it would begin to fall during 2023, closing the year at 5.7%. These forecasts are subject to significant uncertainty, especially regarding the future behavior of external cost shocks, the degree of indexation of nominal contracts and decisions made regarding the domestic price of fuels. Economic activity continues to outperform expectations, and the technical staff’s growth projections for 2022 have been revised upwards from 5% to 6.9%. The new forecasts suggest higher output levels that would continue to exceed the economy’s productive capacity for the remainder of 2022. Economic growth during the first quarter was above that estimated in April, while economic activity indicators for the second quarter suggest that the GDP could be expected to remain high, potentially above that of the first quarter. Domestic demand is expected to maintain a positive dynamic, in particular, due to the household consumption quarterly growth, as suggested by vehicle registrations, retail sales, credit card purchases and consumer loan disbursement figures. A slowdown in the machinery and equipment imports from the levels observed in March contrasts with the positive performance of sales and housing construction licenses, which indicates an investment level similar to that registered for the first three months of the year. International trade data suggests the trade deficit would be reduced as a consequence of import levels that would be lesser than those observed in the first quarter, and stable export levels. For the remainder of the year and 2023, a deceleration in consumption is expected from the high levels seen during the first half of the year, partially as a result of lower repressed demand, tighter domestic financial conditions and household available income deterioration due to increased inflation. Investment is expected to continue its slow recovery while remaining below pre-pandemic levels. The trade deficit is expected to tighten due to projected lower domestic demand dynamics, and high prices of oil and other basic goods exported by the country. Given the above, economic growth in the second quarter of 2022 would be 11.5%, and for 2022 and 2023 an annual growth of 6.9% and 1.1% is expected, respectively. Currently, and for the remainder of 2022, the output gap would be positive and greater than that estimated in April, and prices would be affected by demand pressures. These projections continue to be affected by significant uncertainty associated with global political tensions, the expected adjustment of monetary policy in developed countries, external demand behavior, changes in country risk outlook, and the future developments in domestic fiscal policy, among others. The high inflation levels and respective expectations, which exceed the target of the world's main central banks, largely explain the observed and anticipated increase in their monetary policy interest rates. This environment has tempered the growth forecast for external demand. Disruptions in value chains, rising international food and energy prices, and expansionary monetary and fiscal policies have contributed to the rise in inflation and above-target expectations seen by several of Colombia’s main trading partners. These cost and price shocks, heightened by the effects of Russia's invasion of Ukraine, have been more prevalent than expected and have taken place within a set of output and employment recovery, variables that in some countries currently equal or exceed their projected long-term levels. In response, the U.S. Federal Reserve accelerated the pace of the benchmark interest rate increase and rapidly reduced liquidity levels in the money market. Financial market actors expect this behavior to continue and, consequently, significantly increase their expectations of the average path of the Fed's benchmark interest rate. In this setting, the U.S. dollar appreciated versus the peso in the second quarter and emerging market risk measures increased, a behavior that intensified for Colombia. Given the aforementioned, for the remainder of 2022 and 2023, the Bank's technical staff increased the forecast trajectory for the Fed's interest rate and reduced the country's external demand growth forecast. The projected oil price was revised upward over the forecast horizon, specifically due to greater supply restrictions and the interruption of hydrocarbon trade between the European Union and Russia. Global geopolitical tensions, a tightening of monetary policy in developed economies, the increase in risk perception for emerging markets and the macroeconomic imbalances in the country explain the increase in the projected trajectory of the risk premium, its trend level and the neutral real interest rate1. Uncertainty about external forecasts and their consequent impact on the country's macroeconomic scenario remains high, given the unpredictable evolution of the conflict between Russia and Ukraine, geopolitical tensions, the degree of the global economic slowdown and the effect the response to recent outbreaks of the pandemic in some Asian countries may have on the world economy. This macroeconomic scenario that includes high inflation, inflation forecasts, and expectations above 3% and a positive output gap suggests the need for a contractionary monetary policy that mitigates the risk of the persistent unanchoring of inflation expectations. In contrast to the forecasts of the April report, the increase in the risk premium trend implies a higher neutral real interest rate and a greater prevailing monetary stimulus than previously estimated. For its part, domestic demand has been more dynamic, with a higher observed and expected output level that exceeds the economy’s productive capacity. The surprising accelerations in the headline and core inflation reflect stronger and more persistent external shocks, which, in combination with the strength of aggregate demand, indexation, higher inflation expectations and exchange rate pressures, explain the upward projected inflation trajectory at levels that exceed the target over the next two years. This is corroborated by the inflation expectations of economic analysts and those derived from the public debt market, which continued to climb and currently exceed 3%. All of the above increase the risk of unanchoring inflation expectations and could generate widespread indexation processes that may push inflation away from the target for longer. This new macroeconomic scenario suggests that the interest rate adjustment should continue towards a contractionary monetary policy landscape. 1.2. Monetary policy decision Banco de la República’s Board of Directors (BDBR), at its meetings in June and July 2022, decided to continue adjusting its monetary policy. At its June meeting, the BDBR decided to increase the monetary policy rate by 150 basis points (b.p.) and its July meeting by majority vote, on a 150 b.p. increase thereof at its July meeting. Consequently, the monetary policy interest rate currently stands at 9.0% . 1 The neutral real interest rate refers to the real interest rate level that is neither stimulative nor contractionary for aggregate demand and, therefore, does not generate pressures that lead to the close of the output gap. In a small, open economy like Colombia, this rate depends on the external neutral real interest rate, medium-term components of the country risk premium, and expected depreciation. Box 1: A Weekly Indicator of Economic Activity for Colombia Juan Pablo Cote Carlos Daniel Rojas Nicol Rodriguez Box 2: Common Inflationary Trends in Colombia Carlos D. Rojas-Martínez Nicolás Martínez-Cortés Franky Juliano Galeano-Ramírez Box 3: Shock Decomposition of 2021 Forecast Errors Nicolás Moreno Arias

Macroeconomic summary Annual inflation continued to rise in the first quarter (8.5%) and again outpaced both market expectations and the technical staff’s projections. Inflation in major consumer price index (CPI) baskets has accelerated year-to-date, rising in March at an annual rate above 3%. Food prices (25.4%) continued to contribute most to rising inflation, mainly affected by a deterioration in external supply and rising costs of agricultural inputs. Increases in transportation prices and in some utility rates (energy and gas) can explain the acceleration in regulated items prices (8.3%). For its part, the increase in inflation excluding food and regulated items (4.5%) would be the result of shocks in supply and external costs that have been more persistent than expected, the effects of indexation, accumulated inflationary pressures from the exchange rate, and a faster-than-anticipated tightening of excess productive capacity. Within the basket excluding food and regulated items, external inflationary pressures have meaningfully impacted on goods prices (6.4%), which have been accelerating since the last quarter of 2021. Annual growth in services prices (3.8%) above the target rate is due primarily to food away from home (14.1%), which was affected by significant increases in food and utilities prices and by a rise in the legal monthly minimum wage. Housing rentals and other services prices also increased, though at rates below 3%. Forecast and expected inflation have increased and remain above the target rate, partly due to external pressures (prices and costs) that have been more persistent than projected in the January report (Graphs 1.1 and 1.2). Russia’s invasion of Ukraine accentuated inflationary pressures, particularly on international prices for certain agricultural goods and inputs, energy, and oil. The current inflation projection assumes international food prices will increase through the middle of this year, then remain high and relatively stable for the remainder of 2022. Recovery in the perishable food supply is forecast to be less dynamic than previously anticipated due to high agricultural input prices. Oil prices should begin to recede starting in the second half of the year, but from higher levels than those presented in the previous report. Given the above, higher forecast inflation could accentuate indexation effects and increase inflation expectations. The reversion of a rebate on value-added tax (VAT) applied to cleaning and hygiene products, alongside the end of Colombia’s COVID-19 health emergency, could increase the prices of those goods. The elimination of excess productive capacity on the forecast horizon, with an output gap close to zero and somewhat higher than projected in January, is another factor to consider. As a consequence, annual inflation is expected to remain at high levels through June. Inflation should then decline, though at a slower pace than projected in the previous report. The adjustment process of the monetary policy rate wouldcontribute to pushing inflation and its expectations toward the target on the forecast horizon. Year-end inflation for 2022 is expected to be around 7.1%, declining to 4.8% in 2023. Economic activity again outperformed expectations. The technical staff’s growth forecast for 2022 has been revised upward from 4.3% to 5% (Graph 1.3). Output increased more than expected in annual terms in the fourth quarter of 2021 (10.7%), driven by domestic demand that came primarily because of private consumption above pre-pandemic levels. Investment also registered a significant recovery without returning to 2019 levels and with mixed performance by component. The trade deficit increased, with significant growth in imports similar to that for exports. The economic tracking indicator (ISE) for January and February suggested that firstquarter output would be higher than previously expected and that the positive demand shock observed at the end of 2021 could be fading slower than anticipated. Imports in consumer goods, retail sales figures, real restaurant and hotel income, and credit card purchases suggest that household spending continues to be dynamic, with levels similar to those registered at the end of 2021. Project launch and housing starts figures and capital goods import data suggest that investment also continues to recover but would remain below pre-pandemic levels. Consumption growth is expected to decelerate over the year from high levels reached over the last two quarters. This would come amid tighter domestic and external financial conditions, the exhaustion of suppressed demand, and a deterioration of available household income due to increased inflation. Investment is expected to continue to recover, while the trade deficit should tighten alongside high oil and other export commodity prices. Given all of the above, first-quarter economic growth is now expected to be 7.2% (previously 5.2%) and 5.0% for 2022 as a whole (previously 4.3%). Output growth would continue to moderate in 2023 (2.9%, previously 3.1%), converging similar to long-term rates. The technical staff’s revised projections suggest that the output gap would remain at levels close to zero on the forecast horizon but be tighter than forecast in January (Graph 1.4). These estimates continue to be affected by significant uncertainty associated with geopolitical tensions, external financial conditions, Colombia’s electoral cycle, and the COVID-19 pandemic. External demand is now projected to grow at a slower pace than previously expected amid increased global inflationary pressures, high oil prices, and tighter international financial conditions than forecast in January. The Russian invasion of Ukraine and its inflationary effects on prices for oil and certain agricultural goods and inputs accentuated existing global inflationary pressures originating in supply restrictions and increased international costs. A decline in the supply of Russian oil, low inventory levels, and continued production limits on behalf of the Organization of Petroleum Exporting Countries and its allies (OPEC+) can explain increased projected oil prices for 2022 (USD 100.8/barrel, previously USD 75.3) and 2023 (USD 86.8/barrel, previously USD 71.2). The forecast trajectory for the U.S. Federal Reserve (Fed) interest rate has increased for this and next year to reflect higher real and expected inflation and positive performance in the labormarket and economic activity. The normalization of monetary policy in various developed and emerging market economies, more persistent supply and cost shocks, and outbreaks of COVID-19 in some Asian countries contributed to a reduction in the average growth outlook for Colombia’s trade partners for 2022 (2.8%, previously 3.3%) and 2023 (2.4%, previously 2.6%). In this context, the projected path for Colombia’s risk premium increased, partly due to increased geopolitical global tensions, less expansionary monetary policy in the United States, an increase in perceived risk for emerging markets, and domestic factors such as accumulated macroeconomic imbalances and political uncertainty. Given all the above, external financial conditions are tighter than projected in January report. External forecasts and their impact on Colombia’s macroeconomic scenario continue to be affected by considerable uncertainty, given the unpredictability of both the conflict between Russia and Ukraine and the pandemic. The current macroeconomic scenario, characterized by high real inflation levels, forecast and expected inflation above 3%, and an output gap close to zero, suggests an increased risk of inflation expectations becoming unanchored. This scenario offers very limited space for expansionary monetary policy. Domestic demand has been more dynamic than projected in the January report and excess productive capacity would have tightened more quickly than anticipated. Headline and core inflation rose above expectations, reflecting more persistent and important external shocks on supply and costs. The Russian invasion of Ukraine accentuated supply restrictions and pressures on international costs. This partly explains the increase in the inflation forecast trajectory to levels above the target in the next two years. Inflation expectations increased again and are above 3%. All of this increased the risk of inflation expectations becoming unanchored and could generate indexation effects that move inflation still further from the target rate. This macroeconomic context also implies reduced space for expansionary monetary policy. 1.2 Monetary policy decision Banco de la República’s board of directors (BDBR) continues to adjust its monetary policy. In its meetings both in March and April of 2022, it decided by majority to increase the monetary policy rate by 100 basis points, bringing it to 6.0% (Graph 1.5).

Macroeconomic summary Economic activity has recovered faster than projected, and output is now expected to return to pre-pandemic levels earlier than anticipated. Economic growth projections for 2021 and 2022 have been revised upward, though significant downward bias remains. (Graph 1.1). Colombia’s economy returned to recovery in the third quarter after significant supply shocks and a third wave of COVID-19 in the second. Negative shocks affecting mobility and output were absent in the third quarter, and some indicators of economic activity suggest that the rate of recovery in demand, primarily in consumption, outpaced estimates from the July Monetary Policy Report (MPR) in the context of widely expansive monetary policy. Several factors are expected to continue to contribute to output recovery for the rest of the year and into 2022, including the persistence of favorable international financial conditions, an expected improvement in external demand, and an increase in terms of trade. Increasing vaccination rates, the expectation of higher levels of employment and the consequent effect on household income, improved investment performance (which has not yet returned to pre-pandemic levels), and the expected stimulus from monetary policy that would continue to be expansive should also drive economic activity. As a result, output is estimated to have returned to its pre-pandemic level in the third quarter (previously expected in the fourth quarter). Growth is expected to decelerate in 2022, with excess productive capacity projected to close faster than anticipated in the previous report. Given the above, GDP growth projections have been revised upward for 2021 (9.8%, range between 8.4% and 11.2%) and 2022 (4.7%, range between 0.7% and 6.5%). If these estimates are confirmed, output would have grown by 2.3% on average between 2020 and 2022. This figure would be below long-term sustainable growth levels projected prior to the pandemic. The revised growth forecast for 2022 continues to account for a low basis of comparison from this year (reflecting the negative effects of COVID-19 and roadblocks in some parts of the country), and now supposes that estimated consumption levels for the end of 2021 will remain relatively stable in 2022. Investment and net exports are expected to recover at a faster pace than estimated in the previous report. Nevertheless, the downward risks to these estimates remain unusually significant, for several reasons. First, they do not suppose significant negative effects on the economy from possible new waves of COVID-19. Second, because private consumption, which has already surpassed pre-pandemic levels by a large margin, could perform less favorably than estimated in this forecast should it reflect a temporary phenomenon related to suppressed demand as service sectors re-open (e.g. tourism) and private savings accumulated during the pandemic are spent. Third, disruptions to supply chains could be more persistent than contemplated in this report and could continue to affect production costs, with a negative impact on the economy. Finally, the accumulation of macroeconomic imbalances could translate to increased vulnerability to changes in international financial conditions or in international and domestic economic agents’ perception of risk in the Colombian economy, representing a downward risk to growth. A higher-than-expected increase in inflation, the persistence of supply shocks, and reduced excess productive capacity have led to an increase in inflation projections above the target on the forecast horizon (Graph 1.2). Inflation increased above expectations to 4.51% in the third quarter, due in large part to the price behavior of foods and regulated items, and to a lesser extent to core inflation. Increased international prices and costs continue to generate upward pressure on various sub-baskets of the consumer price index (CPI), as has the partial reversion of some price relief measures implemented in 2020 in response to the COVID-19 pandemic.

Macroeconomic summary Several factors contributed to an increase in projected inflation on the forecast horizon, keeping it above the target rate. These included inflation in December that surpassed expectations (5.62%), indexation to higher inflation rates for various baskets in the consumer price index (CPI), a significant real increase in the legal minimum wage, persistent external and domestic inflationary supply shocks, and heightened exchange rate pressures. The CPI for foods was affected by the persistence of external and domestic supply shocks and was the most significant contributor to unexpectedly high inflation in the fourth quarter. Price adjustments for fuels and certain utilities can explain the acceleration in inflation for regulated items, which was more significant than anticipated. Prices in the CPI for goods excluding food and regulated items also rose more than expected. This was partly due to a smaller effect on prices from the national government’s VAT-free day than anticipated by the technical staff and more persistent external pressures, including via peso depreciation. By contrast, the CPI for services excluding food and regulated items accelerated less than expected, partly reflecting strong competition in the communications sector. This was the only major CPI basket for which prices increased below the target inflation rate. The technical staff revised its inflation forecast upward in response to certain external shocks (prices, costs, and depreciation) and domestic shocks (e.g., on meat products) that were stronger and more persistent than anticipated in the previous report. Observed inflation and a real increase in the legal minimum wage also exceeded expectations, which would boost inflation by affecting price indexation, labor costs, and inflation expectations. The technical staff now expects year-end headline inflation of 4.3% in 2022 and 3.4% in 2023; core inflation is projected to be 4.5% and 3.6%, respectively. These forecasts consider the lapse of certain price relief measures associated with the COVID-19 health emergency, which would contribute to temporarily keeping inflation above the target on the forecast horizon. It is important to note that these estimates continue to contain a significant degree of uncertainty, mainly related to the development of external and domestic supply shocks and their ultimate effects on prices. Other contributing factors include high price volatility and measurement uncertainty related to the extension of Colombia’s health emergency and tax relief measures (such as the VAT-free days) associated with the Social Investment Law (Ley de Inversión Social). The as-yet uncertain magnitude of the effects of a recent real increase in the legal minimum wage (that was high by historical standards) and high observed and expected inflation, are additional factors weighing on the overall uncertainty of the estimates in this report. The size of excess productive capacity remaining in the economy and the degree to which it is closing are also uncertain, as the evolution of the pandemic continues to represent a significant forecast risk. margin, could be less dynamic than expected. And the normalization of monetary policy in the United States could come more quickly than projected in this report, which could negatively affect international financing costs. Finally, there remains a significant degree of uncertainty related to the duration of supply chocks and the degree to which macroeconomic and political conditions could negatively affect the recovery in investment. The technical staff revised its GDP growth projection for 2022 from 4.7% to 4.3% (Graph 1.3). This revision accounts for the likelihood that a larger portion of the recent positive dynamic in private consumption would be transitory than previously expected. This estimate also contemplates less dynamic investment behavior than forecast in the previous report amid less favorable financial conditions and a highly uncertain investment environment. Third-quarter GDP growth (12.9%), which was similar to projections from the October report, and the fourth-quarter growth forecast (8.7%) reflect a positive consumption trend, which has been revised upward. This dynamic has been driven by both public and private spending. Investment growth, meanwhile, has been weaker than forecast. Available fourth-quarter data suggest that consumption spending for the period would have exceeded estimates from October, thanks to three consecutive months that included VAT-free days, a relatively low COVID-19 caseload, and mobility indicators similar to their pre-pandemic levels. By contrast, the most recently available figures on new housing developments and machinery and equipment imports suggest that investment, while continuing to rise, is growing at a slower rate than anticipated in the previous report. The trade deficit is expected to have widened, as imports would have grown at a high level and outpaced exports. Given the above, the technical staff now expects fourth-quarter economic growth of 8.7%, with overall growth for 2021 of 9.9%. Several factors should continue to contribute to output recovery in 2022, though some of these may be less significant than previously forecast. International financial conditions are expected to be less favorable, though external demand should continue to recover and terms of trade continue to increase amid higher projected oil prices. Lower unemployment rates and subsequent positive effects on household income, despite increased inflation, would also boost output recovery, as would progress in the national vaccination campaign. The technical staff expects that the conditions that have favored recent high levels of consumption would be, in large part, transitory. Consumption spending is expected to grow at a slower rate in 2022. Gross fixed capital formation (GFCF) would continue to recover, approaching its pre-pandemic level, though at a slower rate than anticipated in the previous report. This would be due to lower observed GFCF levels and the potential impact of political and fiscal uncertainty. Meanwhile, the policy interest rate would be less expansionary as the process of monetary policy normalization continues. Given the above, growth in 2022 is forecast to decelerate to 4.3% (previously 4.7%). In 2023, that figure (3.1%) is projected to converge to levels closer to the potential growth rate. In this case, excess productive capacity would be expected to tighten at a similar rate as projected in the previous report. The trade deficit would tighten more than previously projected on the forecast horizon, due to expectations of an improved export dynamic and moderation in imports. The growth forecast for 2022 considers a low basis of comparison from the first half of 2021. However, there remain significant downside risks to this forecast. The current projection does not, for example, account for any additional effects on economic activity resulting from further waves of COVID-19. High private consumption levels, which have already surpassed pre-pandemic levels by a large margin, could be less dynamic than expected. And the normalization of monetary policy in the United States could come more quickly than projected in this report, which could negatively affect international financing costs. Finally, there remains a significant degree of uncertainty related to the duration of supply chocks and the degree to which macroeconomic and political conditions could negatively affect the recovery in investment. External demand for Colombian goods and services should continue to recover amid significant global inflation pressures, high oil prices, and less favorable international financial conditions than those estimated in October. Economic activity among Colombia’s major trade partners recovered in 2021 amid countries reopening and ample international liquidity. However, that growth has been somewhat restricted by global supply chain disruptions and new outbreaks of COVID-19. The technical staff has revised its growth forecast for Colombia’s main trade partners from 6.3% to 6.9% for 2021, and from 3.4% to 3.3% for 2022; trade partner economies are expected to grow 2.6% in 2023. Colombia’s annual terms of trade increased in 2021, largely on higher oil, coffee, and coal prices. This improvement came despite increased prices for goods and services imports. The expected oil price trajectory has been revised upward, partly to supply restrictions and lagging investment in the sector that would offset reduced growth forecasts in some major economies. Elevated freight and raw materials costs and supply chain disruptions continue to affect global goods production, and have led to increases in global prices. Coupled with the recovery in global demand, this has put upward pressure on external inflation. Several emerging market economies have continued to normalize monetary policy in this context. Meanwhile, in the United States, the Federal Reserve has anticipated an end to its asset buying program. U.S. inflation in December (7.0%) was again surprisingly high and market average inflation forecasts for 2022 have increased. The Fed is expected to increase its policy rate during the first quarter of 2022, with quarterly increases anticipated over the rest of the year. For its part, Colombia’s sovereign risk premium has increased and is forecast to remain on a higher path, to levels above the 15-year-average, on the forecast horizon. This would be partly due to the effects of a less expansionary monetary policy in the United States and the accumulation of macroeconomic imbalances in Colombia. Given the above, international financial conditions are projected to be less favorable than anticipated in the October report. The increase in Colombia’s external financing costs could be more significant if upward pressures on inflation in the United States persist and monetary policy is normalized more quickly than contemplated in this report. As detailed in Section 2.3, uncertainty surrounding international financial conditions continues to be unusually high. Along with other considerations, recent concerns over the potential effects of new COVID-19 variants, the persistence of global supply chain disruptions, energy crises in certain countries, growing geopolitical tensions, and a more significant deceleration in China are all factors underlying this uncertainty. The changing macroeconomic environment toward greater inflation and unanchoring risks on inflation expectations imply a reduction in the space available for monetary policy stimulus. Recovery in domestic demand and a reduction in excess productive capacity have come in line with the technical staff’s expectations from the October report. Some upside risks to inflation have materialized, while medium-term inflation expectations have increased and are above the 3% target. Monetary policy remains expansionary. Significant global inflationary pressures and the unexpected increase in the CPI in December point to more persistent effects from recent supply shocks. Core inflation is trending upward, but remains below the 3% target. Headline and core inflation projections have increased on the forecast horizon and are above the target rate through the end of 2023. Meanwhile, the expected dynamism of domestic demand would be in line with low levels of excess productive capacity. An accumulation of macroeconomic imbalances in Colombia and the increased likelihood of a faster normalization of monetary policy in the United States would put upward pressure on sovereign risk perceptions in a more persistent manner, with implications for the exchange rate and the natural rate of interest. Persistent disruptions to international supply chains, a high real increase in the legal minimum wage, and the indexation of various baskets in the CPI to higher inflation rates could affect price expectations and push inflation above the target more persistently. These factors suggest that the space to maintain monetary stimulus has continued to diminish, though monetary policy remains expansionary. 1.2 Monetary policy decision Banco de la República’s board of directors (BDBR) in its meetings in December 2021 and January 2022 voted to continue normalizing monetary policy. The BDBR voted by a majority in these two meetings to increase the benchmark interest rate by 50 and 100 basis points, respectively, bringing the policy rate to 4.0%.