Journal articles: 'Demography – Econometric models'

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Braz-Golgher, André. "Associations between household arrangements for couples and satisfaction with life." Papeles de Población 27, no. 109 (December 31, 2021): 91–118. http://dx.doi.org/10.22185/24487147.2021.109.23.

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This paper investigated the relationship between marital arrangements and satisfaction with life in Brazil. Initially, household arrangements with couples in Brazil were classified into seven different groups: one for marriage or relationships indistinguishable from marriage, and six for consensual unions. This allowed the paper to empirically address the natural heterogeneity of marriage and cohabitation and their relationship to levels of satisfaction with life. Then, taking into account the fact that these associations are plagued by endogeneity, econometric models addressed whether the different household arrangements were correlated with different levels of satisfaction with life. After this, the reverse link was also analyzed with the use of econometric models. The results suggest that household arrangement types were weakly or non-significantly correlated with the levels of life satisfaction. Conversely, life satisfaction levels were significant-ly correlated with the different types of household arrangements.

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CARP, Ana. "Models of Analysis of the Social Security System’s Financial Balance." New Challenges in Accounting and Finance 2 (September 2019): 1–10. http://dx.doi.org/10.32038/ncaf.2019.02.01.

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The financial balance of each country's social security system is a concern for countries, professional groups, and individuals. If the first social security systems were based on the principle of social solidarity and objectively the financial resources collected from the active generations were sufficient to cover the risks of the social security branches, nowadays the supporters of this principle are fewer. An objective problem is also the achievement of the system maturity state that occurs after 60-70 years after the scheme’s development that is almost after a period equal to a generation’s age. For the projection of social security models, demographic, economic, fiscal and legislative variables are typically used. In this article, the researcher approached the social security models. Since between social security and demography there is a biunique relationship, the researcher presented econometric and OLG models.

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Aguilar Gutiérrez, Genaro. "Capacidad tributaria y finanzas públicas metropolitanas en México / Fiscal Capacity and Metropolitan Public Finances in Mexico." Estudios Demográficos y Urbanos 25, no. 1 (January 1, 2010): 103. http://dx.doi.org/10.24201/edu.v25i1.1369.

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En este artículo se examinan los factores determinantes de la capacidad tributaria del Distrito Federal y 25 municipios en tres zonas metropolitanas de México. Se presentan algunos modelos que han sido formulados en la literatura internacional de frontera para cuantificar el potencial de obtención de recursos tributarios. Su principal contribución consiste en aplicar un modelo econométrico robusto, el Modelo de Frontera Estocástica, para medir la capacidad de obtención de recursos fiscales en tres zonas metropolitanas de México y cuantificar el grado de esfuerzo fiscal desplegado por 25 municipios y el Distrito Federal durante el periodo 1992-2007. AbstractThis article examines the factors that determine the tax capacity of the Federal District and 25 municipalities in three metropolitan zones in Mexico. The author presents models that have been formulated in international frontier literature to determine the potential for obtaining tax resources. His main contribution involves implementing a robust econometric model, the Stochastic Frontier Model to measure the capacity for obtaining resources in three metropolitan zones in Mexico and determine the degree of fiscal effort made by 25 municipalities and the Federal District during the period from 1992 to 2007.

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Andrei, Jean Vasile, Luminita Chivu, Rodica-Manuela Gogonea, Silvia Elena Iacob, Aurelia Patrascu, Constanta Popescu, Mile Vasic, and Marian Zaharia. "BUSINESS DEMOGRAPHY AND ECONOMIC GROWTH: SIMILARITIES AND DISPARITIES IN 10 EUROPEAN UNION COUNTRIES." Journal of Business Economics and Management 22, no. 5 (August 30, 2021): 1160–88. http://dx.doi.org/10.3846/jbem.2021.15067.

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The main research aim is to investigate and test the long-term existence of a balanced relationship (cointegration) between business demographics and economic growth, expressed in terms of real GDP per capita, and to estimate the econometric models expressing relationships between analyzed variables in European economy. Our The study has focused on ten out of the eleven former communist countries, currently members of the European Union, during the 2006–2016 time period. Croatia was left out due to the shortness of the time series available for it, that the study would have required. These findings have significant implications in designing and shaping the future business models in European former communist countries, and increase convergence. The results obtained confirm the existence of long-term balanced relationships between the variables examined, the forms of which however vary from one cluster of states to another.

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Andrei, Jean Vasile, Luminita Chivu, Ileana Georgiana Gheorghe, Aleksandar Grubor, Teodor Sedlarski, Violeta Sima, Jonel Subić, and Mile Vasic. "Small and Medium-Sized Enterprises, Business Demography and European Socio-Economic Model: Does the Paradigm Really Converge?" Journal of Risk and Financial Management 14, no. 2 (February 4, 2021): 64. http://dx.doi.org/10.3390/jrfm14020064.

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Although the European business environment induces important premises and assures conditions in determining economic growth and social well-being, the determinant and existent connections between the evolution of small and medium-sized enterprises (SMEs), business demography characteristics and the European socio-economic model have been scarcely studied in recent years. The dimensions of the European socio-economic model design a very specific framework in developing business demography and assuring a favorable environment for future SME development. The main aim of the manuscript is to investigate the evolution of the European SMEs sector and the perspective of business demography evolution to converge with exigencies of the European socio-economic model. In order to argue the research objective, eight specific and representative business demography variables were employed, from 12 European Union member states (EU-MS), during 2009–2017. Further, the SMEs’ performances, determined by changing the economic functional paradigm, were assessed. For proving this, an econometric model was designed considering labor productivity as an endogenous variable. Our preliminary analysis shows considerable differences in business demography indicators and SMEs development among all five socio-economic sub-models of the main European socio-economic model, proving a tight connection between European socio-economic models and SMEs’ performance and arguing the necessity of a paradigm convergence. Within some sub-models, there is clear evidence of clustering and convergence in terms of business demography and SMEs future development.

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Kuethe, Todd Henry. "International Real Estate Review." International Real Estate Review 14, no. 1 (April 30, 2011): 118–29. http://dx.doi.org/10.53383/100136.

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This study evaluates the ability of a range of popular aggregate house price indexes to predict house prices out-of- sample at the transaction level for a small geographic area. The analysis particularly addresses the utility of spatial econometric methods. The results suggest that spatial econometric methods, which more explicitly consider the spatial aspects of observed house prices, provide better predictive accuracy as compared to more traditional estimation techniques, such as the repeat sales index, a hybrid repeat sales-hedonic price index, and hedonic price models estimated through least squares. The conclusions are drawn from a sample of 38,984 single-family residential real estate transactions for the city of Milwaukee, Wisconsin over the years 2002-2008.

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Tikhomirov, N. P., and T. M. Tikhomirova. "ASSESSING AND MANAGING THE REPRODUCTION POTENTIAL OF RUSSIA." Federalism, no. 3 (September 16, 2019): 51–71. http://dx.doi.org/10.21686/2073-1051-2019-3-51-71.

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At present Russian Federation in a whole and most of its regions face the problem of justifying the social and economic policy, that ensures the shift from prolonged depopulation to the regime of expanded reproduction of the population. The proposed methodology for such a justification is based on the designing the econometric models, that describe the patterns of objective indicators of population’s natural movement intensity, depending on the main “material” factors, determining the characteristics of its demographic behavior (standard of living, health care expenditures, payments for children, etc.). As such indicators, it is proposed to use the marginal growth rate or its refined modifications, which are calculated only on the basis of sex-age-specific fertility and mortality rates and do not depend on changes in age structures. Such marginal indicators more reliably characterize the potential of self-reproduction of the population in comparison to the total and standardized fertility and mortality rates, commonly used in demography and corresponding to them population growth rates. The paper presents estimates of the marginal rates of natural movement of the Russian population in 1990—2017, which indicate, that the decline in the potential of demographic self-reproduction in the last decade of the 20th century in Russia was quite significant, and the rate of its recovery in the 21st century was not high enough, thus, as a consequence, by 2017 the country had not yet shifted to the regime of expanded reproduction, although in some of its regions such a regime had already been established in 2007—2012. The econometric model, presented in the work, reflecting the dependence of the marginal growth rate of Russian population on the standard of living and the expenditures on demographic policy measures, shows that the shift of the country as a whole to the regime of sustainable extended demographic self-reproduction is possible by 2025—2030, subject to a 2—3% annual increase in the levels of these factors.

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Raya, Josep Maria. "Evaluating Different Housing Prices: Marketing and Financial Distortions." International Real Estate Review 24, no. 4 (December 31, 2021): 549–76. http://dx.doi.org/10.53383/100330.

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The aim of this paper is to evaluate the importance of housing price. We compare the evolution of three different types of housing prices (list, sale and appraisal prices). The objective is to see the marketing and financial consequences of using each type of housing price. To do this, a dataset of a real estate company and its financial intermediary with all of these types of housing prices is used. We estimate econometric models in which the dependent variables are: price (appraisal, selling or list), mark-up, loan to value and foreclosures. The results show evidence of the consequences of using a specific housing price in terms of inflation calculation, financial assets, and collateral valuation and mortgage default, among others.

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Al-Abduljader, Sulaiman T. "International Real Estate Review." International Real Estate Review 22, no. 1 (March 31, 2019): 83–108. http://dx.doi.org/10.53383/100276.

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Regional interdependence among the real estate markets in the Gulf Cooperation Council (GCC) is tested by using a variety of techniques. Econometric tests that involve error correction, symmetric/asymmetric autoregressive distributed lag (ARDL) and structural time series models are utilized. The results reveal the absence of long-run relationships, thus indicating cross-sectional efficiency. However, strong evidence is found for both short and long-run dynamic interdependence when the model allows for asymmetric responses. Finally, the results from the structural time series modeling show that a weak form of interdependence is present, which partly shows that other factors of significant impact explain for the real estate fluctuation other than the corresponding prices of the neighboring countries. Plausible fiscal and monetary policy recommendations are presented.

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Kolosnitsyna, Marina G., and Mikhail Yu Chubarov. "Spread of COVID-19 in the Russian regions in 2020: factors of excess mortality." Population and Economics 6, no. 4 (December 6, 2022): 1–20. http://dx.doi.org/10.3897/popecon.6.e87739.

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The paper identifies major factors associated with the pandemic spread in the Russian regions, using econometric models and nonlinear «Random Forest» models to assess their significance. The study is based on data of the Russian regions for March-December 2020, a balanced panel sample included 780 observations. Prevalence of the pandemic was estimated based on the excess mortality rate. The study has identified a positive relationship between excess mortality and the share of migrants and a negative relationship between excess mortality and the share of pensioners in the region. Importance of climatic factors has been confirmed: high temperatures, other things being equal, reduce excess mortality, while high humidity, on the contrary, increases it. Excess mortality is higher in the regions with lower population mobility. Mortality is higher in the regions with high per capita incomes and regions with significant unemployment. Vice versa, excess mortality is lower in the regions with better doctor and nurse staffing levels. The study results show that in case of repeated waves of the epidemic or emergence of new viruses, public health policy should be geographically differentiated. Priority should be given to epidemiological situation in the regions with humid climate and low temperatures, high incomes, intensive migration, and high unemployment rates. Significant investments in medical education, higher number of medical specialists and their more even distribution across regions are required. This approach turns out to be more effective in terms of reducing mortality rather than restrictions on population mobility.

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Cellini, Marco, Fabrizio Pecoraro, Michael Rigby, and Daniela Luzi. "Comparative analysis of pre-Covid19 child immunization rates across 30 European countries and identification of underlying positive societal and system influences." PLOS ONE 17, no. 8 (August 3, 2022): e0271290. http://dx.doi.org/10.1371/journal.pone.0271290.

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This study provides a macro-level societal and health system focused analysis of child vaccination rates in 30 European countries, exploring the effect of context on coverage. The importance of demography and health system attributes on health care delivery are recognized in other fields, but generally overlooked in vaccination. The analysis is based on correlating systematic data built up by the Models of Child Health Appraised (MOCHA) Project with data from international sources, so as to exploit a one-off opportunity to set the analysis within an overall integrated study of primary care services for children, and the learning opportunities of the ‘natural European laboratory’. The descriptive analysis shows an overall persistent variation of coverage across vaccines with no specific vaccination having a low rate in all the EU and EEA countries. However, contrasting with this, variation between total uptake per vaccine across Europe suggests that the challenge of low rates is related to country contexts of either policy, delivery, or public perceptions. Econometric analysis aiming to explore whether some population, policy and/or health system characteristics may influence vaccination uptake provides important results—GDP per capita and the level of the population’s higher education engagement are positively linked with higher vaccination coverage, whereas mandatory vaccination policy is related to lower uptake rates. The health system characteristics that have a significant positive effect are a cohesive management structure; a high nurse/doctor ratio; and use of practical care delivery reinforcements such as the home-based record and the presence of child components of e-health strategies.

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Hsueh, Li-Min, and Chih-Lung Yen. "International Real Estate Review." International Real Estate Review 12, no. 1 (April 30, 2009): 62–87. http://dx.doi.org/10.53383/100105.

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In this study, we follow the female in a cohort analysis of her housing choices in Taiwan, using data from the population and housing census for 1980, 1990 and 2000. In addition to looking at the female population as a whole, we also compare the differences between females who are heads of households and those who are not. Econometric models focusing on the tenure choice of housing and living space per person are estimated simultaneously. The age effects show that households have the highest homeownership rate and lowest amount of living space per person in their middle years. This is due to persons in their middle years having the highest accumulated wealth and also the largest household size during their life cycle. However, no clear trend can be found in the male sample with respect to the age effect in their middle years, for instance, 25-60, for both homeownership and living space. Hence, the female is probably more suitable than the male in terms of representing a household during its life-cyle. The birth cohort effect shows that the earlier a female is born, the higher is the probability that she will become a homeowner and occupy a larger living space. This result can also be found in studies on male cohorts. These findings thus raise our concerns over the disadvantages that the younger generation faces in becoming homeowners. In addition, we find that the age and birth cohort effects are very different for female-headed and non-female-headed households. Although on average, the female heads have more years of education and higher job participation rates, they have lower homeownership rates. They also benefit less from economic growth. Nevertheless, the gap between the female-headed and non-female-headed households has narrowed as the birth cohort has become younger.

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Frazier, Christopher, and Kara M. Kockelman. "Spatial Econometric Models for Panel Data." Transportation Research Record: Journal of the Transportation Research Board 1902, no. 1 (January 2005): 80–90. http://dx.doi.org/10.1177/0361198105190200110.

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Cities are constantly evolving, complex systems, and modeling them, both theoretically and empirically, is a complicated task. However, understanding the manner in which developed regions change over time and space can be important for transportation researchers and planners. In this paper, methodologies for modeling developed areas are presented, and spatial and temporal effects of the data are incorporated into the methodologies. The work emphasizes spatial relationships between various geographic, land use, and demographic variables that characterize fine zones across regions. It derives and combines land cover data for the Austin, Texas, region from a panel of satellite images and U.S. Census of Population data. Models for population, vehicle ownership, and developed, residential, and agricultural land cover are estimated; the effects of space and time on the models are shown to be statistically significant. Simulations of population and land cover for the year 2020 help to illustrate the strengths and limitations of the models.

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Lee, Ronald D., and Antoine Bommier. "Overlapping generations models with realistic demography." Journal of Population Economics 16, no. 1 (February 1, 2003): 135–60. http://dx.doi.org/10.1007/s001480100102.

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Vencálek, Ondřej, Karel Hron, and Peter Filzmoser. "A comparison of generalised linear models and compositional models for ordered categorical data." Statistical Modelling 20, no. 3 (January 15, 2019): 249–73. http://dx.doi.org/10.1177/1471082x18816540.

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Ordered categorical data occur in many applied fields, such as geochemistry, econometrics, sociology and demography or even transportation research, for example, in the form of results from various questionnaires. There are different possibilities for modelling proportions of individual categories. Generalised linear models (GLMs) are traditionally used for this purpose, but also methods of compositional data analysis (CoDa) can be considered. Here, both approaches are compared in depth. Particularly, different assumptions of the models on variability are highlighted. Advantages and disadvantages of individual models are pointed out. While the CoDa model may be inappropriate when the variability of the compositional coordinates depends on the regressors, for example, due to different total counts on which the coordinates are based, the GLM may underestimate the uncertainty of the predictions considerably in case of large-scale data.

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Kasprzyk, Beata. "Application of econometric models to measure the satisfaction with wages and salaries." Wiadomości Statystyczne. The Polish Statistician 63, no. 4 (April 27, 2018): 33–57. http://dx.doi.org/10.5604/01.3001.0014.0644.

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The article presents the results of the research attempting to make a statistical analysis of subjective perception of wages and salaries as the main component of household income, using a specific econometric modelling. It was examined whether certain socio-demographic determinants could be identified and, if so, to what extent they could influence the subjective sense of satisfaction with wage and salaries. The research was conducted on the basis of data collected using a survey method in 2015 for a random sample of households in Podkarpackie voivodship, where wages and salaries are among the lowest in the country. The binomial models used to explain the qualitative variable depending on the level of exogenous variables (qualitative and quantitative) were compared. Logit and probit regression models made it possible to determine the probability of success as a chance of a positive response, i.e. (in relation to the scope of the research) a state of satisfaction with obtained wages and salaries.

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Baker, T. Brent, and Raymond G. Deardorf. "Development and Application of a Revenue and Ridership Forecasting Model for Ferry Service." Transportation Research Record: Journal of the Transportation Research Board 1608, no. 1 (January 1997): 40–46. http://dx.doi.org/10.3141/1608-05.

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A combination of statistical approaches is used to develop near-to mid-range ridership and revenue forecasting models for Washington State Ferries for use in quarterly budget updates. Econometric regression models use historical and forecast trends in state economic and demographic variables to project systemwide ridership by six fare categories for different fare scenarios. Time series analysis models are used to project ferry ridership at the individual route level by six fare categories. The sum of the time series route forecasts is then calibrated to the econometric systemwide totals to yield unconstrained ridership forecasts by route and fare category. A capacity constraint model handles cases where the demand for vehicle travel exceeds vessel capacity by generating ridership ceilings for different service scenarios. Finally, the appropriate fares are applied to the ridership projections to arrive at revenue forecasts over a 10-year horizon.

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Anacka, Marta, and Anna Janicka. "Population forecast for Poland based on econometric forecasts of migration flows." Wiadomości Statystyczne. The Polish Statistician 63, no. 8 (August 28, 2018): 5–27. http://dx.doi.org/10.5604/01.3001.0014.0686.

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The aim of this article is to present the results of a population forecast for Poland for the years 2015—2060, based on an econometric model of migration flows. This approach differs from existing forecasts and projections in three significant ways: the projected population are residents, the four migration flows (i.e. inflow and outflow divided into foreigners and Polish citizens) are estimated with econometric tools and the uncertainty of the obtained estimates is taken into account (in a formal manner). The results obtained indicate consistency of the applied econometric models of migration flows with theories of migration. Immigration to Poland is expected to intensify during the next four decades. Depopulation as well as ageing are expected nevertheless, although the pace of these two phenomena will be slower than predicted in other demographic analyses.

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Zholudeva, Vera V. "Econometric modeling of the higher education system in Yaroslavl region." Open Education 22, no. 4 (August 28, 2018): 12–20. http://dx.doi.org/10.21686/1818-4243-2018-4-12-20.

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The objective of the study is to analyze the models that describe the processes, running in the education. The article concludes that currently there are important changes and new trends in the sphere of higher education in Russia: the development of higher education is carried out in the conditions of the effective use of modern information technologies. The author emphasized the analysis of the use of distance learning technologies in the higher education system, which is especially important for our country because of the vast territory, the remoteness of many regions from the centers of educational services, due to the growing high cost of these services.The development of Internet technologies, multimedia in conjunction with the growing popularity, the Internet makes it possible to promote education to a new level. That is why today the demand for distance learning in Russia is equal, and in some universities has exceeded the demand for full-time education. In the near future distance learning will take on the main burden in the system of professional training and retraining of specialists due to its mobility, mass, availability and relative cheapness.Also in this article the basic quantitative regularities of the market of higher education of the Yaroslavl region in relation to the economy are determined. In the article, econometric modeling is chosen as a tool for management in the field of vocational education. This is due to the fact that it is able to identify trends and patterns of changes in the indicators of education development in the region, to determine the consequences of a development strategy that contributes to the understanding of the processes taking place in the higher education system. Econometric models, used for forecasting in the education system are analyzed; their advantages and disadvantages are revealed. Some of them are disclosed in the paper on the example of modeling the system of higher education in the Yaroslavl region.As the result of analyzing the statistical data of the regional office of Federal State Statistics Service in Yaroslavl region the following models were developed: a model that shows how the application of distance technologies in higher education is related to socio-economic indicators; the regression model of correlation between the system of higher education and the economy (GRP); the model of forecasting the number of students in different educational categories; the econometrical model of connectivity between the education expenditures and economic factors. The paper evaluates the impact of educational and demographic indicators on the education level index of the Yaroslavl region. The econometrical models, constructed in the research, represent the informational basis for modernization of regional higher education system and elaboration of social-economic strategies of the regional development. The proposed statistical tools of evaluation and forecasting education system development can be used for decision-making and planning on the regional level.

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Gillen, Benjamin J., Sergio Montero, Hyungsik Roger Moon, and Matthew Shum. "BLP-2LASSO for aggregate discrete choice models with rich covariates." Econometrics Journal 22, no. 3 (July 11, 2019): 262–81. http://dx.doi.org/10.1093/ectj/utz010.

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Summary We introduce the BLP-2LASSO model, which augments the classic BLP (Berry, Levinsohn, and Pakes, 1995) random-coefficients logit model to allow for data-driven selection among a high-dimensional set of control variables using the 'double-LASSO' procedure proposed by Belloni, Chernozhukov, and Hansen (2013). Economists often study consumers’ aggregate behaviour across markets choosing from a menu of differentiated products. In this analysis, local demographic characteristics can serve as controls for market-specific preference heterogeneity. Given rich demographic data, implementing these models requires specifying which variables to include in the analysis, an ad hoc process typically guided primarily by a researcher’s intuition. We propose a data-driven approach to estimate these models, applying penalized estimation algorithms from the recent literature in high-dimensional econometrics. Our application explores the effect of campaign spending on vote shares in data from Mexican elections.

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Pośpiech, Ewa Katarzyna, and Adrianna Mastalerz-Kodzis. "Application of Spatial Regression in Employment Characteristics Modelling." Acta Universitatis Lodziensis. Folia Oeconomica 3, no. 335 (May 16, 2018): 63–74. http://dx.doi.org/10.18778/0208-6018.335.05.

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The article analyses the employment characteristics. The employment rate was studied in selected regions of Europe, and subsequently, for selected variables: total population employed, women employed and men employed, classic econometric models were constructed and the necessity of including the spatial factor in the process of modelling was verified. The demographic variables and GDP per capita were chosen as explaining variables of the model. It was analysed whether including a spatial approach in the models would improve their quality. Two basic spatial models were taken into consideration: the spatial error model and the spatial lag model, the former of which turned out to be the right tool for the analyses.

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Haque, Ismail, Dipendra Nath Das, and Priyank Pravin Patel. "Reading the geography of India’s district-level fertility differentials: a spatial econometric approach." Journal of Biosocial Science 51, no. 5 (August 8, 2019): 745–74. http://dx.doi.org/10.1017/s0021932019000087.

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AbstractIndia has gradually progressed into fertility transition over the last few decades. However, the timing and pace of this transition has varied notably in terms of both its geography and the demographic groups most affected by it. While much literature exists on the relationships between fertility level and its influence on demographic, economic, socio-cultural and policy-related factors, the potential spatial variations in the effects of these factors on the fertility level remain unaddressed. Using the most recent district-level census data (of 2011) for India, this nationwide study has identified plausible spatial dependencies and heterogeneities in the relationships between the district-wise Total Fertility Rates (TFRs) and their respective demographic, socioeconomic and cultural factors. After developing a geocoded database for 621 districts of India, spatial regression and Geographically Weighted Regression (GWR) models were used to decipher location-based relationships between the district-level TFR and its driving forces. The results revealed that the relationships between the district-level TFR and the considered selected predictors (percentage of Muslims, urbanization, caste group, female mean age at marriage, female education, females in the labour force, net migration, sex ratio at birth and exposure to mass media) were not spatially invariant in terms of their respective strength, magnitude and direction, and furthermore, these relationships were conspicuously place- and context-specific. This study suggests that such locality-based variations and their complexities cannot be explained simply by a single narrative of either socioeconomic advancement or government policy interventions. It therefore contributes to the ongoing debate on fertility research in India by highlighting the spatial dependence and heterogeneity of the impacts made by demographic, socioeconomic and cultural factors on local fertility levels. From a methodological perspective, the study also discerns that the GWR local model performs better, in terms of both model performance and prediction accuracy, compared with the conventional global model estimates.

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Chang, Kuang-Liang, Nan-Kuang Chen, and Charles Leung. "International Real Estate Review." International Real Estate Review 19, no. 4 (December 31, 2016): 435–92. http://dx.doi.org/10.53383/100229.

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This paper revisits the relationships among macroeconomic variables and asset returns. Based on recent developments in econometrics, we categorize competing models of asset returns into different "Equivalence Predictive Power Classes" (EPPCs). During the pre-crisis period (1975-2005), some models emphasize that imperfect capital markets outperform an AR(1) for the forecast of housing returns. After 2006, a model that includes both an external finance premium (EFP) and the TED spread "learns and adjusts" faster than competing models. Models that encompass GDP experience a significant decay in predictive power. We also demonstrate that a simulation-based approach is complementary to the EPPC methodology.

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Ahn, SoEun, Andrew J. Plantinga, and Ralph J. Alig. "Determinants and Projections of Land Use in the South Central United States." Southern Journal of Applied Forestry 26, no. 2 (May 1, 2002): 78–84. http://dx.doi.org/10.1093/sjaf/26.2.78.

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Abstract This article presents historical trends and future projections of forest, agricultural, and urban/other land uses for the South Central region of the United States. An econometric land use model is used to investigate the relationship between the areas of land in alternative uses and economic and demographic factors influencing land use decisions. Determinants of land use included in the model are the net returns from different land uses, land quality, and demographic variables such as population density. Given projections of stumpage prices and population, the fitted econometric models are used to generate projections of future land use to the year 2050. Under a scenario in which population changes in the future, but stumpage prices remain constant, urban/other land increases by 2.2 million ac from 1992 to 2050. More private timberland (1.8 million ac) than agricultural land (0.4 million ac) is converted to urban/other land to accommodate the population increase. Under a scenario of population growth and 0.5% annual increases in stumpage prices, private timberland increases from 101.7 million ac to 107.2 million ac by 2050, and the urban/other land increases by 1.3 million ac. Agricultural land declines by almost 7 million ac, mirroring the increases in the urban/other land and private timberland. South. J. Appl. For. 26(2):78–84.

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Arroyo, Cristino R., and Junsen Zhang. "Dynamic microeconomic models of fertility choice: A survey." Journal of Population Economics 10, no. 1 (April 2, 1997): 23–65. http://dx.doi.org/10.1007/s001480050030.

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Melkersson, Maria, and Dan-Olof Rooth. "Modeling female fertility using inflated count data models." Journal of Population Economics 13, no. 2 (July 6, 2000): 189–203. http://dx.doi.org/10.1007/s001480050133.

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Lasoń, Aleksandra, and Andrzej Torój. "Anti-liberal, anti-establishment or constituency-driven? Spatial econometric analysis of polish parliamentary election results in 2015." European Spatial Research and Policy 26, no. 2 (December 31, 2019): 199–236. http://dx.doi.org/10.18778/1231-1952.26.2.10.

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We investigated the spatial variation patterns of voting results in Polish parliamentary election in 2015 across 380 regions. That election was a milestone event in Polish politics that substantially affected Poland’s internal and foreign policy directions and promoted two emerging political parties as runners-up against the well-established ones. While socio-economic, cultural and geographical factors such as economic activity, historical legacies (post-Russian East vs post-German West) and economic dichotomies (cities vs the countryside) explain most variations for most parties, they do not appeared to fit as determinants of the new parties’ support, especially of right-wing populists. Demographic target groups of individual parties appear to be relatively unresponsive to their pre-election offerings. The spatial specification of econometric models considerably improves their statistical properties. We also examined mixed-W models to account for the unobservable spatial effects stemming from the construction of constituencies. Their distinctive sets of candidates added significantly to the explanation of the spatial variation in voting.

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Higgins, Patrick, Julie L. Hotchkiss, and Ellyn Terry. "Evolution of Behavior, Uncertainty, and the Difficulty of Predicting Labor Force Participation." Business and Economic Research 9, no. 4 (November 6, 2019): 157. http://dx.doi.org/10.5296/ber.v9i4.15350.

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This paper demonstrates the difficulty of forecasting labor force participation (LFP) rates by showing that a random walk does just as well as select sophisticated econometric models in predicting short-term aggregate LFP. Most efforts to improve forecasts of LFP focus on fine-tuning predictions of determinants (i.e., demographics and labor market conditions). However, we show that even perfect knowledge of future demographic trends and labor market conditions is not enough to overcome the additional difficulty posed by changes in behavior over time. Behavior in this paper refers to the way in which demographics and labor market conditions impact labor supply decisions (i.e., parameter coefficients).

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Dharmasena, Senarath, Oral Capps, and Annette Clauson. "Ascertaining the Impact of the 2000 USDA Dietary Guidelines for Americans on the Intake of Calories, Caffeine, Calcium, and Vitamin C from At-Home Consumption of Nonalcoholic Beverages." Journal of Agricultural and Applied Economics 43, no. 1 (February 2011): 13–27. http://dx.doi.org/10.1017/s1074070800004028.

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Obesity is one of the most pressing and widely emphasized health problems in America today. Beverage choices made by households have impacts on determining the intake of calories, calcium, caffeine, and vitamin C. Using data from the Nielsen Homescan Panel over the period 1998-2003, and a two-way random-effects Fuller-Battese error components procedure, we estimate econometric models to examine economic and demographic factors affecting per-capita daily intake of calories, calcium, caffeine, and vitamin C derived from the consumption of nonalcoholic beverages. Our study demonstrates the effectiveness of the USDA 2000 Dietary Guidelines in reducing caloric and nutrient intake associated with nonalcoholic beverages.

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Akram, Naeem. "Determinants of Domestic Violence in Pakistan: A Qualitative and Econometric Analysis." Partner Abuse 12, no. 3 (July 1, 2021): 265–94. http://dx.doi.org/10.1891/pa-d-20-00006.

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Domestic violence exists in every country, irrespective of the culture, ethnicity, age, income, and education of the women. World Health Organization has estimated that approximately 35% of women worldwide had experienced sexual or physical violence. The present study has attempted to analyze the role of different socioeconomic indicators on the prevalence of domestic violence. In this regard, data of Pakistan Demographic and Health Survey 2017–2018 has been used and logit models have been estimated. It has been found that women married below the age of 18; living in rural areas; have more children; whose mothers experienced violence; feared their husbands; with little or no autonomy in decision-making; had a bank account; married outside of the family; and had not inherited any land or property were significantly more vulnerable victims of domestic violence. It has been found that women's education, education of her husband, and exposure to media by creating awareness may protect women from domestic violence. Furthermore, working women are more likely to face domestic violence, but women who have started working before marriage are significantly less vulnerable victims of domestic violence. However, the age of women herself, the age of husband, age of household head and wealth of household, living in the nucleus or joint family, receiving any support from Benazir Income Support Program (BISP) have no significant role in determining the domestic violence in Pakistan.

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Moffatt, Peter G., and Simon A. Peters. "Grouped zero-inflated count data models of coital frequency." Journal of Population Economics 13, no. 2 (July 6, 2000): 205–20. http://dx.doi.org/10.1007/s001480050134.

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Mayer, Jochen, and Regina T. Riphahn. "Fertility assimilation of immigrants: Evidence from count data models." Journal of Population Economics 13, no. 2 (July 6, 2000): 241–61. http://dx.doi.org/10.1007/s001480050136.

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Melich-Iwanek, Krystyna. "ECONOMIC ACTIVITY OF THE POPULATION IN THE SILESIAN VOIVODSHIP IN THE BACKGROUND OF DEMOGRAPHIC DEVELOPMENT." Zeszyty Naukowe Wyższej Szkoły Humanitas Zarządzanie 23, no. 1 (March 31, 2022): 51–74. http://dx.doi.org/10.5604/01.3001.0015.8609.

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The aim of the article is to analyze, from statistical and econometric perspectives, the dynamics of economic activity of the population of the Silesian Voivodeship in particular, an attempt at a statistical measurement of the impact of select phenomena conditioning the labor market. Key considerations are preceded by a presentation the historical and current demographic situation in the voivodeship. Problems of foreign and inter-voivodeship migrations, the aging of population of the province were investigated. Moreover, impact of social policies on the labor market was analyzed, including the “Family 500+” program as well as regulations concerning retirement age. The study utilizes quantitative methods of time series analysis, including the time series models taking into account the occurrence of turning points. The results of research show, that in the near future, the demographic situation of the Silesian Voivodeship will not improve,, the lowering of retirement age is a threat to the labor market, the “500+” program not only did not influence a rise in fertility rate but lowered the rate of economic activity of women.

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Brezis, Elise S. "Can demographic transition only be explained by altruistic and neo-Malthusian models?" Journal of Socio-Economics 39, no. 2 (April 2010): 233–40. http://dx.doi.org/10.1016/j.socec.2009.11.001.

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Ravulaparthy, Srinath K., Brent Selby, Arun Kuppam, Kyunghwi Jeon, Sreevatsa Nippani, and Vladimir Livshits. "Spatial Firm Demographic Microsimulator: Development and Validation for Phoenix and Tucson, Arizona, Megaregion." Transportation Research Record: Journal of the Transportation Research Board 2671, no. 1 (January 2017): 59–70. http://dx.doi.org/10.3141/2671-07.

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Integrated land use and transportation models address regional issues related to congestion, mobility, and economic competitiveness. Essential to this is freight transport in the form of economic vitality, along with distribution and complex interactions between various stakeholders. Within this context, it is critical to capture and describe accurately the behavioral dynamics of these stakeholders (or firms) in the region, including modeling firm demographic events of birth, death, growth–decline, and migration patterns. This study presents a framework for modeling firm demographics with a microsimulation approach as applicable to the Phoenix and Tucson, Arizona, megaregion. The spatial firm demographic microsimulator makes use of the National Establishment Time Series database of business establishments and thereby evolves them over time and space from 2007 to 2012. A series of econometric models is estimated to simulate the firm events that consider determinants such as firm internal attributes (size, age, and growth) and external attributes. Empirical results from the simulation suggest that events of death and relocation are driven primarily by changes in firm internal attributes such as employment size or growth rates. Additionally, locational impacts such as agglomeration economies and access to transportation infrastructure trigger these events. The simulation results presented in this study are validated further with observed firm demographic trends along with microlevel zonal employment estimated with various goodness-of-fit measures. The firm demographic microsimulator model presented in this study is unique, as this is one of the first large-scale implementations for a megaregion in the United States within the context of simulating demand for commercial transportation.

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Wu, Song, and Yu. "Spatial Differences in China’s Population Aging and Influencing Factors: The Perspectives of Spatial Dependence and Spatial Heterogeneity." Sustainability 11, no. 21 (October 25, 2019): 5959. http://dx.doi.org/10.3390/su11215959.

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Since China became an aging society in 2000, the regional inequality of population aging has been highlighted, and the phenomenon of “aging before getting rich” has gradually become a core issue in China’s coordinated socioeconomic development. This paper aims to comprehensively assess the spatial differences and driving forces of China’s population aging through two-stage nested Theil decomposition, ESDA, and spatial econometric models. Empirical results show that spatial differences in population aging were evident at different spatial scales, and the distribution gradually decreased from east to west, showing a positive spatial correlation of similar value aggregation. Moreover, China’s population aging was determined by the demographic, socioeconomic, and natural environment, and there are different leading factors in different regions. The demographic aspects played a decisive role and had a direct influence, while the socioeconomic and natural environment indirectly affected population aging through demographic factors and became the root cause of regional differences in population aging. These findings provide an empirical basis for establishing a cooperative mechanism and formulating a targeted response to the problem of population aging in various regions in China.

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Preston, Ian, and Ian Walker. "Welfare measurement in labour supply models with nonlinear budget constraints." Journal of Population Economics 12, no. 3 (August 17, 1999): 343–61. http://dx.doi.org/10.1007/s001480050103.

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Sakhbetdinova, Kamilya. "Determinants of fertility in Russian families." Moscow University Economics Bulletin 2020, no. 6 (December 30, 2020): 104–23. http://dx.doi.org/10.38050/01300105202066.

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Competent demographic policy implies an understanding by the state of the economic, social, and demographic processes taking place in society. In earlier Russian and foreign studies, the authors found a number of fertility factors, however, the direction of influence of such determinants could be opposite. Aware of the special influence of sociocultural attitudes and values of the population on the number of children in a family, the author made an attempt to identify the determinants of fertility based on an empirical study of the World Values Survey. Using statistical and econometric methods, models that reflect the determinants of fertility in modern Russia were constructed. This work revealed a positive effect on the birth rate of religiosity, traditional views and the importance of the family for the respondent. Inversely related to the number of children in a family such factors as the level of education of the population and the value of leisure.

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Melich-Iwanek, Krystyna. "ECONOMIC ACTIVITY OF THE POPULATION IN POLAND – SELECTED PROBLEMS AND CONDITIONS." Zeszyty Naukowe Wyższej Szkoły Humanitas Zarządzanie 22, no. 3 (September 30, 2021): 9–28. http://dx.doi.org/10.5604/01.3001.0015.4216.

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The aim of the article is to analyze, from statistical and econometric perspectives, the dynamics of Poles’ economic activity, in particular, an attempt at a statistical measurement of the impact of select phenomena conditioning the labor market. Key considerations are preceded by a presentation the historical and current demographic situation in Poland. Problems of foreign migration and the aging of the Polish society were investigated. Moreover, impact of social policies on the labor market was analyzed, including the “Family 500+” program as well as regulations concerning retirement age. The study utilizes quantitative methods of time series analysis, including the time series models taking into account the occurrence of turning points. The results of research show, that: in the near future the Polish demographic situation will not improve, the lowering of retirement age is a threat to the labor market, the “500+” program not only did not influence a rise in fertility rate but lowered the rate of economic activity of women.

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40

Kalabikhina, Irina, Zarina Kazbekova, German Klimenko, and Anton Kolotusha. "Demographic regional rankings by media activity on maternal (family) capital." Applied Econometrics 67, no. 3 (2022): 46–73. http://dx.doi.org/10.22394/1993-7601-2022-67-46-73.

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Based on autoregressive models of distributed lags (ADL models), a sample of publications on maternity (family) capital, using an aggregator Public.ru and the developed list of normative legal acts on maternity capital, the authors assessed the intensity and dynamics of the media reaction to federal legislative initiatives regarding maternal capital, and built demographic rating of Russian regions on the publication activity of electronic media in response to the events of the federal legislative process in the field of maternity capital taking into account the different periodization of the actions of the maternity capital program.

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Winegarden, C. R., and Paula M. Bracy. "Demographic Consequences of Maternal-Leave Programs in Industrial Countries: Evidence from Fixed-Effects Models." Southern Economic Journal 61, no. 4 (April 1995): 1020. http://dx.doi.org/10.2307/1060738.

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Jenkins, Stephen. "THE IMPLICATIONS OF STOCHASTIC DEMOGRAPHIC ASSUMPTIONS FOR MODELS OF THE DISTRIBUTION OF INHERITED WEALTH." Bulletin of Economic Research 37, no. 3 (September 1985): 231–44. http://dx.doi.org/10.1111/j.1467-8586.1985.tb00196.x.

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LE, DIEU THANH, and HAIL PARK. "THE IMPACT OF DEMOGRAPHIC CHANGE ON ECONOMIC GROWTH." Singapore Economic Review 65, no. 02 (August 22, 2019): 471–84. http://dx.doi.org/10.1142/s0217590819500401.

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This paper evaluates the impact of demographic change on the economic growth of OECD and non-OECD countries. An annual panel dataset of 71 countries, consisting of 27 advanced economies and 44 emerging economies over the period of 1981–2014, is used. Two types of regression models (panel regression model and panel continuous threshold model) including several demographic variables are used to investigate the effects of demographic structure. The results of this study show the significant difference of the impact of demographic transition on the economic growth of OECD and non-OECD economies.

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Al-Qudsi, Sulayman. "The demand for children in Arab countries: Evidence from panel and count data models." Journal of Population Economics 11, no. 3 (August 3, 1998): 435–52. http://dx.doi.org/10.1007/s001480050078.

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de la Fuente-Mella, Hanns, Ricardo Campos-Espinoza, Nelson Lay-Raby, Omar Lamelés-Corvalán, Mario Pino-Moya, and Reynier Ramírez-Molina. "Multinomial Cross-Sectional Regression Models to Estimate and Predict the Determinants of Academic Performance: The Case of Auditor Accountant of the Pontifical Catholic University of Valparaíso." Sustainability 14, no. 15 (July 28, 2022): 9232. http://dx.doi.org/10.3390/su14159232.

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The debate on the primary cross-curricular skills or fundamental competencies that must be improved in higher education has increased in the last few years. This is especially important in the new distant learning environments, which bring new challenges to the educational process. Econometric models have been designed to explain the students’ academic performance, which has been measured using their qualifications average, the number of failed subjects, passed subjects, and withdrawn subjects, and the level of progress, among other indicators, to try to understand the influence of variables such as students’ self-esteem, reading comprehension, English proficiency level, and performance in a mathematics-related subject on the students of accountant auditor program from Pontificia Universidad Católica de Valparaiso. Students were asked to fill in a questionnaire to collect data on the psychological and pedagogical variables, while the socio-economic and socio-demographic data were collected from the university. The results have shown that the most significant variables in the development level of this skill type are socio-demographic and socio-economic characteristics. Some of the psychological and pedagogical variables that have, to a lesser degree, some influences are self-regulation in the learning process and the self-perception of anxiety levels. Lastly, some recommendations to intervene in the students’ learning process are presented with the objective of achieving a higher level of development in this type of competences.

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Jenkins, Stephen. "THE IMPLICATIONS OF 'STOCHASTIC DEMOGRAPHIC ASSUMPTIONS FOR MODELS OF THE DISTRIBUTION OF INHERITED WEALTH: CORRECTION." Bulletin of Economic Research 39, no. 2 (April 1987): 185. http://dx.doi.org/10.1111/j.1467-8586.1987.tb00240.x.

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Regan, Tracy L., and Ronald L. Oaxaca. "Work experience as a source of specification error in earnings models: implications for gender wage decompositions." Journal of Population Economics 22, no. 2 (February 16, 2008): 463–99. http://dx.doi.org/10.1007/s00148-007-0180-5.

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Gupta, Sachin, and Pradeep K. Chintagunta. "On Using Demographic Variables to Determine Segment Membership in Logit Mixture Models." Journal of Marketing Research 31, no. 1 (February 1994): 128–36. http://dx.doi.org/10.1177/002224379403100111.

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The authors propose an extension of the logit-mixture model that defines prior segment membership probabilities as functions of concomitant (demographic) variables. Using this approach it is possible to describe how membership in each of the segments, segments being characterized by a specific profile of brand preferences and marketing variable sensitivities, is related to household demographic characteristics. An empirical application of the methodology is provided using A.C. Nielsen scanner panel data on catsup. The authors provide a comparison with the results obtained using the extant methodology in estimation and validation samples of households.

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Boiko, Vitalii, Olha Mulska, Ihor Baranyak, and Olha Levytska. "Ukrainian Migration Aspirations towards Germany: Analysis and Development Scenarios." Comparative Economic Research. Central and Eastern Europe 24, no. 1 (March 30, 2021): 65–84. http://dx.doi.org/10.18778/1508-2008.24.04.

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Based on the multiple regression model and scenario approach to forecasting, the article estimates the Ukrainian migration aspirations towards Germany (the scale of migration, the economic activity of migrants, and their economic benefits). It is argued that major transformations in the gender-age structure of the German population may cause a demographic crisis and labour market imbalances. Our projections indicate the growing role of foreign human resources in the German economy. When modeling the scale of emigration from Ukraine, an integrated approach is applied, considering not only trends of pull-push factors but also special aspects of the German migration policy and the outflow of 8–10 million Ukrainian migrant workers. Given the poor statistical data on the scale of labour emigration needed for constructing reliable econometric models, the use of expert forecasting method remains the most optimal technique for assessing potential migration flows and migration systems.

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Stepanov, Vladimir S. "Assessing SARS-CoV-2-related mortality rate in Russian regions, based on the econometric model." Russian Journal of Infection and Immunity 12, no. 4 (September 9, 2022): 783–89. http://dx.doi.org/10.15789/2220-7619-asr-1846.

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The objects of the study were the daily data on the population morbidity and mortality due to coronavirus disease 2019 (COVID-19) in Russian regions, as well as regional medical, demographic and environmental data recorded in recent years. COVID-19 is a contagious disease caused by the novel coronavirus (SARS-CoV-2). The mathematical methods consist of correlation and regression analysis, methods of testing statistical hypotheses. First, a multiple Variable Structure Regression should be specified. The intercept in the model differs from region to region, depending on the combination of values for dummy variables. The role of the dependent variable Y t was chosen as the cumulative mortality published by the operational headquarters for the regions that has been linked to day t, so that COVID-19 was considered the main cause of death. The complex of explanatory variables included two factorial variables that changed daily, and had a lag relative to t value. Also, this complex included a number of variables that did not change with the growth of t: the explanatory variable with the regions availability with doctors of certain specialties; and four dummy variables. One of them coded the regions belonging to the two southern Russian Federal Districts. Three other variables characterized the increased air pollution in settlements recorded in recent years, as well as the level of radiation pollution of the regions territory and the population health estimated for 10 classes of diseases (for the circulatory system, endocrine system, etc.). The values of such dummy variables were obtained from open data from the Federal State Statistics Service (Rosstat) etc. The model parameters were estimated by the least squares method using the training table, which included 40 Russias regions, the t parameter for variable Y t was assessed starting from November, 1, 2021. As a result, a statistical model was built with an approximation error equal to 3%. For regions of the regions examined this error was 1.94 (1.5)% for the value Y t that has been fixed on the 1st Nov. The plots show daily prediction for mortality rate due to COVID-19 in the first half of November for seven Russian regions compared with actual data. The model can be useful in development of medical and demographic policy in geographic regions, as well as generating adjusted compartment models that based on systems of differential equations (SEIRF, SIRD, etc.).

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Journal articles on the topic 'Demography – Econometric models'

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