Agricultural and Rural Household Income Statistics

Farm Management,

Philadelphia: The State of the City, A 2014 Update

This report is an update to the previous research from the Pew Charitable Trust on the city of Philadelphia. This report includes updates on demographic changes, income statistics, housing statistics, employment information, crime rates, school enrollment trends, and updates on the use of mass transit

The mean-field approximation model of company's income growth

We introduce a mean-field type approximation for description of company's income statistics. Utilizing huge company data we show that a discrete version of Langevin equation with additive and multiplicative noises can appropriately describe the time evolution of a company's income fluctuation in statistical sense. The Zipf's law of income distribution is shown to be hold in a steady-sate widely, and country-dependence of income distribution can also be nicely implemented in our numerical simulation.Comment: 10 pages, 7 figures, submitted to Physics

SAMPLE DESIGN IN THE FINNISH AGRICULTURAL INCOME STATISTICS

The Finnish Agricultural Income Statistics. published yearly by Statistics Finland, are based on a survey in which the data are collected from the farms in connection with taxation. The sampling design is stratified simple random sampling, in which Neyman allocation is used to calculate the sample sizes for the strata. The Farm Register is used as the sampling frame where variables such as region, production sector and arable land are available for stratification. The total incomes of farms from the previous survey serve as the allocation variable. Stratification and Neyman allocation rendered the estimates of most income variables more effective When measured by the design effect (DEFF) values which ranged from 0.3 to 0.7. Ratio estimation was studied by using arable land as an auxiliary variable. The sample was also evaluated by calculating estimates for variables available from administrative records and by companng them with the true values. The estimated values were systematically bigger than the true values. Non-response among small farms was one reason for this systematic error. A comparison by production sector revealed that the biggest differences were in cattle farming and in the production of cereals. An examination of the correlations in these sectors revealed a linear dependence between the survey and auxiliary variables. Ratio estimation was used in these sectors to reduce the error of estimates and to balance the variables known from other sources

Creating a 1995 OHS and a Combined OHS-IES Database in STATA

This paper builds on Technical Paper 2003: 1. It provides a technical description of how the 1995 October Household Survey (OHS) dataset was created in STATA and subsequently merged with the 1995 Income and Expenditure Survey (IES) dataset to form a combined dataset. The combined survey links household-level income statistics from IES 1995 with individual-level employment data from OHS 1995. This linking of data is necessary for the construction of the Social Accounting Matrix (SAM) sub-matrix that links factor income data to household income. Since the same set of households were visited for both surveys it is possible to merge observations using unique household identification numbers. All the STATA do-files are listed in the technical appendix.Consumer/Household Economics,

Material Deprivation in Selected EU Countries According to EU-SILC Income Statistics

The article deals with issues of households at risk of poverty in relative conception. Income poverty means a situation when the threshold of 0.6 of median income is not achieved. The analysis of a broader definition of poverty is based on identification and assessment of material deprivation factors, including: financial stress, housing conditions, availability of consumer durables and basic needs. Data sources are based EU-SILC dataset. Presented analysis is focused on selected EU countries, namely Czech Republic, Finland, France, Spain and United Kingdom. The result identifies the problem areas that cause deprivation symptoms

Better estimates from binned income data: Interpolated CDFs and mean-matching

Researchers often estimate income statistics from summaries that report the number of incomes in bins such as \$0-10,000, \$10,001-20,000,...,\$200,000+. Some analysts assign incomes to bin midpoints, but this treats income as discrete. Other analysts fit a continuous parametric distribution, but the distribution may not fit well. We fit nonparametric continuous distributions that reproduce the bin counts perfectly by interpolating the cumulative distribution function (CDF). We also show how both midpoints and interpolated CDFs can be constrained to reproduce the mean of income when it is known. We compare the methods' accuracy in estimating the Gini coefficients of all 3,221 US counties. Fitting parametric distributions is very slow. Fitting interpolated CDFs is much faster and slightly more accurate. Both interpolated CDFs and midpoints give dramatically better estimates if constrained to match a known mean. We have implemented interpolated CDFs in the binsmooth package for R. We have implemented the midpoint method in the rpme command for Stata. Both implementations can be constrained to match a known mean.Comment: 20 pages (including Appendix), 3 tables, 2 figures (+2 in Appendix

Informal but not Insignificant: Unregistered Workers in North Cyprus

The size of the informal labour force and its contribution to the national income of North Cyprus has been an issue of considerable controversy and political significance. Because of the relatively free movement of labour between Turkey and North Cyprus, a significant body of unregistered workers have accumulated in North Cyprus. The findings are that from 1996 to 2000 the informal employment is between 35 to 40 per cent of the total labour force. Because not all the informal sectors production is excluded from the official national income statistics, the understatement of the official statistics is estimated to be between 12 to 17 percent of GNP. The fiscal losses are estimated to be about 9 percent of total tax revenues and a loss of social security revenues is approximately 38 per cent of the total annual contributions.Cyprus, informal sector, informal labour force, fiscal losses, unrecorded income, underground economy

Incomes and inequality in the long run: the case of German elderly

We employ German Sample Survey Income data to examine income inequality and the financial situation of elderly citizens for the period from 1978 to 2003, focussing on differences between retired and non-retired elderly and between elderly with residence in the Old and the New German Laender. Inter-temporal changes in income inequality are also decomposed by income sources. To our knowledge, this is the first study that provides comparable and detailed longitudinal income statistics for the German elderly. We find some remarkable inter-temporal patterns. First, the financial situation of the elderly has improved substantially over time. This is true especially for the New Laender, although elderly with residence in the Old Laender remain financially privileged. Within the same age cohort, we also find that non-retired, on average, are financially better-off compared to retired elderly. For reunified Germany, inequality is astonishingly stable over time, but rises significantly since 1993 in the New German Laender. --Pensioner,Inequality,Inequality Decomposition,German Sample Survey Income data