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Статті в журналах з теми "Income distribution"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 1 серпня 2024

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1

Khakhulina, Liudmila A., and Milan Tuček. "Income Distribution." Sociological Research 35, no. 1 (January 1996): 20–32. http://dx.doi.org/10.2753/sor1061-0154350120.

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2

Ravi Kanbur, S. M., and Jan-Olov Stromberg. "Income transitions and income distribution dominance." Journal of Economic Theory 45, no. 2 (August 1988): 408–16. http://dx.doi.org/10.1016/0022-0531(88)90278-5.

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3

Lambert, Sue. "Income Distribution Surveys." Australian Economic Review 29, no. 3 (July 1996): 320–26. http://dx.doi.org/10.1111/j.1467-8462.1996.tb00938.x.

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4

Stark, Oded, Fryderyk Falniowski, and Marcin Jakubek. "Consensus Income Distribution." Review of Income and Wealth 63, no. 4 (February 17, 2017): 899–911. http://dx.doi.org/10.1111/roiw.12291.

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5

Khamnei, Hossein Jabbari, Sajad Nikannia, Masood Fathi, and Shahryar Ghorbani. "Modeling income distribution: An econophysics approach." Mathematical Biosciences and Engineering 20, no. 7 (2023): 13171–81. http://dx.doi.org/10.3934/mbe.2023587.

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<abstract><p>This study aims to develop appropriate models for income distribution in Iran using the econophysics approach for the 2006–2018 period. For this purpose, the three improved distributions of the Pareto, Lognormal, and Gibbs-Boltzmann distributions are analyzed with the data extracted from the target household income expansion plan of the statistical centers in Iran. The research results indicate that the income distribution in Iran does not follow the Pareto and Lognormal distributions in most of the study years but follows the generalized Gibbs-Boltzmann distribution function in all study years. According to the results, the generalized Gibbs-Boltzmann distribution also properly fits the actual data distribution and could clearly explain the income distribution in Iran. The generalized Gibbs-Boltzmann distribution also fits the actual income data better than both Pareto and Lognormal distributions.</p></abstract>

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6

Kalleitner, Fabian, and Sandra Bohmann. "The Inequity Z: Income Fairness Perceptions in Europe across the Income Distribution." Socius: Sociological Research for a Dynamic World 9 (January 2023): 237802312311671. http://dx.doi.org/10.1177/23780231231167138.

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Using data from the European Social Survey, we examine income fairness evaluations of 17,605 respondents from 28 countries. Respondents evaluated the fairness of their own incomes as well as the fairness of the incomes of the top and bottom income deciles in their countries. Depicted on a single graph, these income fairness evaluations take on a Z-shaped form, which we call the “inequity Z”. The inequity Z reveals an extensive level of consensus within each country regarding the degree of unfairness of top and bottom incomes. With rising income, respondents consistently judge their own incomes to be less unfair. Across countries, the gap in fairness ratings between top and bottom incomes rises with income inequality. Perceived underreward of bottom incomes is more pronounced in countries where bottom incomes are objectively lower. Thus, this visualization suggests that, when people are confronted with information about actual income levels, perceived inequity increases with inequality.

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7

Findeis, Jill L., and Venkateshwar K. Reddy. "Decomposition of Income Distribution Among Farm Families." Northeastern Journal of Agricultural and Resource Economics 16, no. 2 (October 1987): 165–73. http://dx.doi.org/10.1017/s0899367x00001495.

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The greater reliance of U.S. farm families on off-farm income has implications for the structure of agriculture and the distribution of income within agriculture. Using annual data on farm households from the Current Population Survey, the degree of income inequality for the U.S. and by region is assessed for 1984. The distribution of income among farm families is decomposed by income source. Off-farm income is shown to contribute to higher average incomes and reduce income inequality at the margin, but only in regions where full-time farming predominates. In the Northeast and South, increases in off-farm income increase regional income inequality.

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8

Gradín, Carlos, and Máximo Rossi. "Income Distribution and Income Sources in Uruguay." Journal of Applied Economics 9, no. 1 (May 2006): 49–69. http://dx.doi.org/10.1080/15140326.2006.12040637.

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9

Van Hoa, Tran. "Effects of income distribution on household income." Economics Letters 18, no. 4 (January 1985): 397–99. http://dx.doi.org/10.1016/0165-1765(85)90061-8.

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10

Liu, Chia-Ming. "Income distribution, quality differentiation and product line design." Innovative Marketing 13, no. 1 (May 18, 2017): 24–32. http://dx.doi.org/10.21511/im.13(1).2017.03.

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Анотація:

The purpose of this paper is to characterize the relationship between quality differentiation, income distribution and product line design. According to the findings, the author can explain the trend of quality differentiation and the phenomenon of extreme product diversity in different conditions of income distribution. When the middle class of consumers reach a certain critical few number, the quality for them will descend. Only the high-end and low-end quality left for this extreme condition; that is, the product quality spectrum will shrink. The product quality for middle and low class will gradually get worse and worse, even lower than original quality. The product line design will be reconsidered to the opposite extremes.

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11

Trzcińska, Kamila. "An Analysis of Household Income in Poland and Slovakia Based on Selected Income Models." Folia Oeconomica Stetinensia 22, no. 1 (June 1, 2022): 287–301. http://dx.doi.org/10.2478/foli-2022-0014.

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Abstract Research background: Studies of income distributions may focus on describing empirical distributions by theoretical models. This approach can be useful for many reasons. When choosing a statistical model, it is important both to find out a theoretical distribution function that would characterize empirical frequency distribution and to choose suitable methods to calculate the parameters of the model. In the literature, there are proposals for various types of mathematical functions. Very high accuracy with empirical distribution is characteristic for Dagum and log-normal models. In 2010 Zenga proposed a new three-parameter model for economic size distribution which possesses interesting statistical properties. Purpose: The aim of this paper is to apply and compare Dagum, log-normal and Zenga models to income distributions in Poland and Slovakia. Research methodology: The studies are based on research data from the European Quality of Life Surveys (EQLS), whose purpose is to measure both objective and subjective indicators of the standard of living of citizens and their households. The estimation parameters were obtained by means of the maximum likelihood method and D’Addario’s invariants method. Results: The results of the conducted approximations, presented in the paper confirmed the good consistency of the Dagum and Zenga distributions with the empirical income distribution of households in Poland and Slovakia. Novelty: The Zenga distribution was used for the first time to describe the income distribution of the Slovak population and it allows the best fit to the empirical data of this country.

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12

Davies, Hugh, and Heather Joshi. "Sex, Sharing and the Distribution of Income." Journal of Social Policy 23, no. 3 (July 1994): 301–40. http://dx.doi.org/10.1017/s0047279400021887.

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ABSTRACTIt is customary to assume that income is redistributed between the sexes within the family. This article investigates alternative assumptions about sharing within the family and their effects on the distribution of income. Using data from the UK Family Expenditure Survey for 1968 and 1986, we contrast two assumptions about sharing within the family; the conventional assumption of equal sharing or ‘pooling’, and an alternative of ‘minimum sharing’. Under each assumption, we examine the composition of extreme quintiles of the income distribution, and compute the numbers of men and women falling below an arbitrary ‘poverty line’. The contribution to inequality of the net transfers between the sexes and other sources of income is also examined. We estimate that resource transfers (other than for housing) between spouses could, if all income is pooled, account for about one third of married couples’ pooled incomes in 1986 and about 56 per cent of the inequality of married women's incomes (in 1968, 56 per cent and 50 per cent respectively). Taking the bottom quintile of pooled income as an arbitrary ‘poverty line’, we calculate that 15 per cent of married people would have been below this line in 1986 if all incomes were pooled. On the minimum sharing assumption, 52 per cent of married women, but only 11 per cent of married men would have been under the line.

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13

Waterman, A. M. C., and Athanasios Asimakopulos. "Theories of Income Distribution." Canadian Journal of Economics 22, no. 2 (May 1989): 454. http://dx.doi.org/10.2307/135686.

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14

Lipton, Michael, Arne Bigsten, and Jacques Lecaillon. "Income Distribution and Development." Economic Journal 95, no. 379 (September 1985): 831. http://dx.doi.org/10.2307/2233065.

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15

Jenkins, Stephen, and John Creedy. "Dynamics of Income Distribution." Economica 54, no. 216 (November 1987): 532. http://dx.doi.org/10.2307/2554191.

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16

Slottje, Daniel J., and John Creedy. "Dynamics of Income Distribution." Journal of the American Statistical Association 82, no. 398 (June 1987): 683. http://dx.doi.org/10.2307/2289490.

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17

Li, Hongyi, Danyang Xie, and Heng-Fu Zou. "Dynamics of income distribution." Canadian Journal of Economics/Revue Canadienne d`Economique 33, no. 4 (November 2000): 937–61. http://dx.doi.org/10.1111/0008-4085.00048.

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18

Galor, Oded, and Joseph Zeira. "Income Distribution and Macroeconomics." Review of Economic Studies 60, no. 1 (January 1993): 35. http://dx.doi.org/10.2307/2297811.

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19

Krugman, Paul. "The Income Distribution Disparity." Challenge 33, no. 4 (July 1990): 4–6. http://dx.doi.org/10.1080/05775132.1990.11471435.

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20

Pasinetti, Luigi L. "Sraffa on income distribution." Cambridge Journal of Economics 12, no. 1 (March 1988): 135–38. http://dx.doi.org/10.1093/oxfordjournals.cje.a035042.

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21

MAHLER, VINCENT A. "Income Distribution within Nations." Comparative Political Studies 22, no. 1 (April 1989): 3–32. http://dx.doi.org/10.1177/0010414089022001001.

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Анотація:

In recent years a large number of cross-national studies have examined the causes and consequences of income inequality within nations. Unfortunately, few of these studies have attended very carefully to problems of measurement and definitional consistency that can seriously undermine the comparative use of currently available data on income shares. This article offers a discussion of the major theoretical and practical problems that can arise in measuring and comparing patterns of income distribution across nations, focusing on the completeness of income coverage, the unit of analysis, the time period over which income is measured, the scope of population coverage, the underreporting of income, and the effect of public sector fiscal policies. It then assesses major published sources of cross-national data on the size distribution of income in light of these problems. Finally, the article offers several suggestions for minimizing the negative consequences of measurement problems that remain in even the best available data on income shares.

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22

Seers, Dudley. "INCOME DISTRIBUTION AND EMPLOYMENT." Institute of Development Studies Bulletin 2, no. 4 (May 22, 2009): 4–10. http://dx.doi.org/10.1111/j.1759-5436.1970.mp2004002.x.

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23

Acemoglu, D., and J. Ventura. "The World Income Distribution." Quarterly Journal of Economics 117, no. 2 (May 1, 2002): 659–94. http://dx.doi.org/10.1162/003355302753650355.

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24

Yilmaz, Ensar, and Sinem Sefil-Tansever. "Income Distribution and Redistribution." Journal of Economic Issues 53, no. 4 (October 2, 2019): 1103–25. http://dx.doi.org/10.1080/00213624.2019.1675449.

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25

Sciortino, John J., John H. Huston, and Roger W. Spencer. "Risk and income distribution." Journal of Economic Psychology 9, no. 3 (September 1988): 399–408. http://dx.doi.org/10.1016/0167-4870(88)90043-8.

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26

Perotti, Roberto. "Income distribution and investment." European Economic Review 38, no. 3-4 (April 1994): 827–35. http://dx.doi.org/10.1016/0014-2921(94)90119-8.

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27

Abouelmagd, et. al., T. H. M. "Characterization of Income Distribution." International Journal of Business and Statistical Analysis 1, no. 1 (July 1, 2014): 45–48. http://dx.doi.org/10.12785/ijbsa/010104.

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28

Milanovic, Branko. "Remittances and Income Distribution." Journal of Economic Studies 14, no. 5 (May 1987): 24–37. http://dx.doi.org/10.1108/eb002657.

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29

Bourguignon, François, William H. Branson, and Jaime de Melo. "Adjustment and income distribution." Journal of Development Economics 38, no. 1 (January 1992): 17–39. http://dx.doi.org/10.1016/0304-3878(92)90016-3.

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30

Mizoguchi, Toshiyuki, and Tateo Yoshida. "Evaluation of Asian Income Distribution and Poverty Ratios Using Worldwide Income Distribution." Asian Economic Journal 12, no. 2 (June 1998): 183–93. http://dx.doi.org/10.1111/1467-8381.00059.

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31

Quevedo Cubillos, Hernando, and María N. Quevedo. "Income distribution in the Colombian economy from an econophysics perspective." Cuadernos de Economía 35, no. 69 (September 1, 2016): 691–707. http://dx.doi.org/10.15446/cuad.econ.v35n69.44876.

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Recently, in econophysics, it has been shown that it is possible to analyze economic systems as equilibrium thermodynamic models. We apply statistical thermodynamics methods to analyze income distribution in the Colombian economic system. Using the data obtained in random polls, we show that income distribution in the Colombian economic system is characterized by two specific phases. The first includes about 90% of the interviewed individuals, and is characterized by an exponential Boltzmann-Gibbs distribution. The second phase, which contains the individuals with the highest incomes, can be described by means of one or two power-law density distributions that are known as Pareto distributions.

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32

Mallick, Seeme. "Sustainable Income, Employment, and Income Distribution in Indonesia." Pakistan Development Review 46, no. 4II (December 1, 2007): 579–96. http://dx.doi.org/10.30541/v46i4iipp.579-596.

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Production and consumption activities in any economy have a direct impact on the environment. Although increased economic activity and population growth in developing countries continue to exert enormous pressure on their natural environments, the role of the environment is neglected in the estimation of national income. Such neglect at the macroeconomic level is at least in part, an important cause of environmental degradation in developing countries. Since the United Nations Conference on Environment and Development in 1992 at Rio and even as early as middle of the 1980s, a substantial literature had developed on methods to integrate the environment into the economic development process. The main assertion in this literature is that natural resources represent a form of capital that is analogous to the stock of manufactured capital. Sustainable income can be determined by allocating a portion of income to allow for the deprecation of natural capital [Ahmed, El Serafy, and Lutz (1989) and Solow (1992)]. Indonesia had average real GDP growth rates of more than five percent per year up to the early 1990s [World Bank (1994)]. But income inequality (measured by the Gini coefficient) has been high. Although inequality continues to be quite high, especially between rural and urban populations, Indonesia has been successful in poverty alleviation up to mid 1990s. In 1976 almost 40 percent of its population was below the poverty line, which in 1993 decreased to less than 14 percent [Todaro (1994)]. Income distributional consequences of economic growth would continue to be one of the main policy issues in Indonesia. This is due to its large population size, presence of different ethnic and religious groups, large diversity between rural and urban groups, variety of natural resources scattered over the country, huge distances and the effects of a far-flung archipelago [Akita, Lukman, and Yamada (1999)].

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33

Willis, Geoff. "Income distribution and income shares: wealth and income distributions explained using generalised Lotka-Volterra SFC ABM models." International Review of Applied Economics 29, no. 6 (July 25, 2015): 816–42. http://dx.doi.org/10.1080/02692171.2015.1065225.

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34

Gang, Gong, and Yang Guang. "Analysis of China's Unequal Income Distribution from the Perspective of Functional Income Distribution." Social Sciences in China 31, no. 4 (November 2010): 53–72. http://dx.doi.org/10.1080/02529203.2010.524366.

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35

Trzcińska, Kamila. "Analysis of Household Income in Poland Based on the Zenga Distribution and Selected Income Inequality Measure." Folia Oeconomica Stetinensia 20, no. 1 (June 1, 2020): 421–36. http://dx.doi.org/10.2478/foli-2020-0025.

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Анотація:

AbstractResearch background: A lot of research has been directed at describing empirical distributions by using a theoretical model. In the literature there are proposals for various types of mathematical functions. In 2010 Zenga proposed a new three-parameter model for economic size distribution which possesses interesting statistical properties which can be used to model income, wealth and financial variables.Purpose: The aim of this paper is to apply the Zenga model to income distributions in Poland by voivodeship.Research methodology: The basis for the calculations presented in the paper has been based on the individual data coming from a random sample obtained within a Household Budget Survey conducted by the central Statistical Office in the year 2014. The parameters estimates of the Zenga distribution were obtained by means of the D’Addario’s invariants methods, mainly with the Pietra index.Results: The results of the conducted approximations, presented in the paper confirmed the good consistency of the Zenga distribution with the empirical income distribution in Poland, both in total and for households.Novelty: The study contributed to the application of a new three-parameter income distribution model to describe income distributions in Poland.

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36

Muszyńska, Joanna, Jarosław Oczki, and Ewa Wędrowska. "Convergence of household incomes in the European Union countries." Wiadomości Statystyczne. The Polish Statistician 63, no. 11 (November 28, 2018): 21–40. http://dx.doi.org/10.5604/01.3001.0014.0722.

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Анотація:

The aim of the study is to verify the hypothesis of a tendency towards levelling of household income in the EU countries in the years 2007—2015. Convergence process of the level and the distribution of household disposable income was analysed. The basic source of information were Eurostat’s data from EU-SILC database. The convergence analysis of income levels was carried out for the mean, median and first decile of annual equivalised household disposable incomes, weighted by country population. To examine their convergence, regression models used in economic convergence analyses were adapted and the concept of absolute ß convergence was used. In the study of income distributions convergence the income distribution in households by decile groups was used, and the degree of their discrepancy was assessed using the generalised form of the Jensen-Shannon divergence measure. The study was conducted for 27 EU countries, 15 of the old EU states and 12 new member states. On the basis of the obtained results, it was concluded that there was no convergence of the distributions of income by quantiles. However, the convergence of the considered characteristics of income distributions (mean, median, first decile) was observed.

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37

Esteban, J. "Income-Share Elasticity and the Size Distribution of Income." International Economic Review 27, no. 2 (June 1986): 439. http://dx.doi.org/10.2307/2526515.

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38

Liu, Jiancheng. "China’s Income Distribution System Reform and Income Growth Strategy." OALib 03, no. 05 (2016): 1–11. http://dx.doi.org/10.4236/oalib.1102660.

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39

Yan, Beiling. "International Trade as Determined by Income and Income Distribution." International Economic Journal 21, no. 4 (December 2007): 633–51. http://dx.doi.org/10.1080/10168730701699141.

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40

Docquier, Frederic. "Income Distribution, Non-convexities and the Fertility-Income Relationship." Economica 71, no. 282 (May 2004): 261–73. http://dx.doi.org/10.1111/j.0013-0427.2004.00369.x.

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41

Saarimaa, Tuukka. "Imputed Rental Income, Taxation and Income Distribution in Finland." Urban Studies 48, no. 8 (November 17, 2010): 1695–714. http://dx.doi.org/10.1177/0042098010377474.

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42

Richiardi, Pelin Sekerler, Marva Corley-Coulibaly, and Hassan Kashef. "Income distribution and middle-income groups across the world." World of Work Report 2013, no. 1 (May 2013): 27–44. http://dx.doi.org/10.1002/wow3.36.

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43

Dutta, Jayasri, J. A. Sefton, and M. R. WEALE. "Income distribution and income dynamics in the United Kingdom." Journal of Applied Econometrics 16, no. 5 (2001): 599–617. http://dx.doi.org/10.1002/jae.620.

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44

Saiful Nathan, Siti Badariah, and M. Mohd Rosli. "Distributional effects of non-farm incomes in a Malaysian rice bowl." International Journal of Social Economics 43, no. 2 (February 8, 2016): 205–20. http://dx.doi.org/10.1108/ijse-09-2013-0200.

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Анотація:

Purpose – The purpose of this paper is to identify the structure of household income and examine the effects of non-farm incomes on the income distribution of farm households in a relatively developed rural area of the Malaysian rice bowl. Design/methodology/approach – The non-farm incomes were disaggregated into different components to determine the contribution of each income source to total household income and overall inequality. The income distribution and decomposition was examined using the Gini decomposition method. Findings – It was found that almost 71 percent of the households in the sample had at least one source of non-farm income. On average, non-farm incomes contributed about 33 percent to total household income. Non-farm wage employment was the dominant source of non-farm income, accounting for almost 26 percent of overall household income. The farm incomes, especially the paddy incomes were found to be the inequality-decreasing income source. The study also confirmed the proposition that the non-farm incomes were the inequality-increasing income source as they contributed up to 35 percent of the overall income inequality. Originality/value – Previous studies have found that non-farm incomes have different effects on income inequality of rural communities, especially those in the rice granary areas situated in less developed states of Malaysia, where poverty is still a problem. This study is significant because it identifies the effect of certain incomes on the overall income inequality among farm households in the granary areas located in a relatively developed rural area. The studied areas are characterized by an intensive paddy production and a rapid development in business and industrial activities, and hence, providing non-farm employment opportunities to the rural farmers. Therefore, this study shows the income structure and how farm and non-farm incomes affect the overall income distribution of the paddy farmers.

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45

Abd Raof, Anis Syazwani, Mohd Azmi Haron, Muhammad Aslam Mohd Safari, and Zailan Siri. "Modeling the Incomes of the Upper-Class Group in Malaysia using New Pareto-Type Distribution." Sains Malaysiana 51, no. 10 (October 31, 2022): 3437–48. http://dx.doi.org/10.17576/jsm-2022-5110-26.

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Анотація:

The new Pareto-type distribution has been previously introduced as an alternative to the conventional Pareto distribution in modeling income distribution. It is claimed to provide better flexibility for mathematical simplicity of probability functions and has a more straightforward mathematical form. In this study, the new Pareto-type distribution is used to model the income of the Malaysian upper-class group. The threshold is determined using the fixed proportion technique and the maximum likelihood estimator method is used to estimate the shape parameter. Then, the goodness-of-fit of the fitted new Pareto model is measured using the coefficient of determination, R2 and Kolmogorov–Smirnov statistics. We also measure the income inequality among the Malaysian top income earners using the Lorenz curve, Gini and Theil indices based on the fitted new Pareto model. Finally, the new Pareto distribution is compared to alternative distributions to analyze which model can give the best fit for the data. Our analysis shows that the Pareto type-1 and the new Pareto models are well fitted to the top income data for all years considered. However, the new Pareto model provides better flexibility which covering more incomes in the upper tail of the distribution than the Pareto type-1 model.

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46

Moya, Cristóbal, Jule Adriaans, and Carsten Sauer. "Unjust Income Inequality Prevails Across 29 Countries." Socius: Sociological Research for a Dynamic World 9 (January 2023): 237802312311715. http://dx.doi.org/10.1177/23780231231171581.

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Анотація:

The aim of this visualization is to describe justice evaluations of income inequality from a cross-country perspective for more than 72,000 respondents in 29 countries. The analyses were based on data from two large, cross-country survey programs. The International Social Survey Programme (ISSP) asked for an evaluation of the overall income distribution, and the European Social Survey (ESS) asked for justice evaluations of both bottom and top incomes. The authors find that injustice of the income distribution prevails in all studied countries except Denmark and that injustice of bottom incomes prevails in all countries. Moreover, in the countries included in both the ISSP and ESS, the share of respondents evaluating the overall income distribution as just always falls between the share evaluating bottom and top incomes as just. These results suggest that depending on the country context, different parts of the distribution (top and bottom incomes) influence its overall evaluation.

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47

Abdul Majid, Muhammad Hilmi, and Kamarulzaman Ibrahim. "Composite Pareto Distributions for Modelling Household Income Distribution in Malaysia." Sains Malaysiana 50, no. 7 (July 31, 2021): 2047–58. http://dx.doi.org/10.17576/jsm-2021-5007-19.

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Анотація:

Composite Pareto distributions are flexible as the models allow for data to be described by two distributions: a Pareto distribution for the data above a threshold value and another separate distribution for data below the threshold value. It is noted in some previous literatures that the Paretian tail behaviour can be observed in the distribution of Malaysian household income. In this paper, the composite Pareto models are fitted to the Malaysian household income data of several years. These fitted composite Pareto models are then compared to several univariate models for describing income distribution using pseudo-likelihood based AIC, BIC and Kolmogorov-Smirnov goodness-of-fit test. It is found that the income distributions in Malaysia can be best described by the lognormal-Pareto (II) model as compared to other candidate models.

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48

Waldmann, R. J. "Income Distribution and Infant Mortality." Quarterly Journal of Economics 107, no. 4 (November 1, 1992): 1283–302. http://dx.doi.org/10.2307/2118389.

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49

Bronfenbrenner, Martin. "Income Distribution and "Economic Justice"." Journal of Economic Education 17, no. 1 (1986): 35. http://dx.doi.org/10.2307/1182273.

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50

Chotikapanich, Duangkamon, William Griffiths, Gholamreza Hajargasht, Wasana Karunarathne, and D. Rao. "Using the GB2 Income Distribution." Econometrics 6, no. 2 (April 18, 2018): 21. http://dx.doi.org/10.3390/econometrics6020021.

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