Per Capita Personal Income Research Articles

Spatial and Non-Spatial Panel Data Estimators: Simulation Study and Application to Personal Income in U.S. States

The spatial analysis aims to understand and explore the nature of entanglements and interactions between spatial units’ locations. The analysis of models involving spatial dependence has received great attention in recent decades. Because ignoring the presence of spatial dependence in the data is very likely to lead to biased or inefficient estimates if we use traditional estimation methods. Therefore, this paper is an attempt to assess the risks involved in ignoring the spatial dependence that characterizes the panel data by using a Monte Carlo simulation (MCS) study for two of the most common spatial panel data (SPD) models; Spatial lag model (SLM) and spatial error model (SEM), by comparing the performance of two estimators; i.e., spatial maximum likelihood estimator (MLE) and non-spatial ordinary least squares (OLS) within-group estimator, across two levels of analysis; Parameter-level in terms of bias and root mean square error (RMSE), and model-level in terms of goodness of fit criteria under different scenarios of spatial units N, time-periods T, and spatial dependence parameters, by using two different structures of spatial weights matrix; inverse distance, and inverse exponential distance. The results show that the non-spatial bias and RMSE of β ̂ are functions of the degree of spatial dependence in the data for both models, i.e., SLM and SEM. If the spatial dependence is small, then the choice of the non-spatial estimator may not lead to serious consequences in terms of bias and RMSE of β ̂. On the contrary, the choice of the non-spatial estimator always leads to has disastrous consequences if the spatial dependence is large. On the other hand, we provide a general framework that shows how to define the appropriate model from among several candidate models through application to a dataset of per capita personal income (PCPI) in U.S. states during the period from 2009 to 2019, concerning three main aspects: educational attainment, economy size, and labour force type. The results confirm that PCPI is spatially dependent lagged correlated.

Determinants of Per Capita Personal Income in the US: Spatial Fixed Effects Panel Data Modeling

Over the last decades, the Per Capita Personal Income (PCPI) variable was a common measure of the effectiveness of economic development policy. Therefore, this paper is an attempt to investigate the determinants of personal income by using spatial panel data models for 48 U.S. states during the period from 2009 to 2017. We utilize the three following models: spatial autoregressive (SAR) model, Spatial Error (SEM) Model, and Spatial Autoregressive Combined (SAC) model, with individual (or spatial) fixe deffects according to three different known methods for constructing spatial weights matrices: binary contiguity, inverse distance, and Gaussian transformation spatial weights matrix. Additionally, we pay attention for direct and indirect effects estimates of the explanatory variables for SAR, SEM, and SAC models. The second objective of this paper is to show how to select the appropriate model to fit our data. The results indicate that the three used spatial weights matrices provide the same result based on goodness of fit criteria, and the SAC model is the most appropriate model among the models presented. However, the SAC model with spatial weights matrix based on inverse distance is better compared to other used models. Also, the results indicate that percentage of individuals with graduate or professional degree, real Gross Domestic Product (GDP) per capita,and number of nonfarm jobs have a positive impact on the PCPI, while the percentage of individuals without degree or bachelor’s degree have a negative impact on the PCPI.

The role of airports in city employment growth, 1950–2010

This study considers the effects of commercial airports on local economies over the post-World War II period (specifically, 1950–2010). To overcome endogeneity concerns, a pooled synthetic control event study strategy is employed on newly digitized historical aviation data to estimate treatment effects on a variety of employment, population, and wage outcomes. I find that airports have led to, on average, 3.9 percent growth in total employment (and 3.4% growth in population) per decade. Over the 30-year period for which wage and air traffic data are available, earnings per worker increased by 2%, and per-capita personal income increased by 3%, corresponding to growth rates of up to 1.2 percent per decade, respectively.

Proportions of macronutrients, including specific dietary fats, in prospective anti-Alzheimer\u2019s diet

Here we present a novel life-long whole-population study, which enabled us to predict a diet that, in terms of macronutrient proportions, may be prophylactic against Alzheimer’s Disease (AD). The method is based on the existence of oscillations in the correlation between historical per capita personal income (PCPI) and age-adjusted death rates (AADR) for AD for each state of the USA in 2005. These oscillations can be explained by changing proportions of macronutrients in the average American diet between 1929 and 2005. We assumed that reducing future correlation of PCPI with AADR will reduce the population’s susceptibility to AD. Based on the results of fitting macronutrient availabilities to the variability of Roriginal, using Generalized Additive Models (GAM) analysis, we constructed four “Calculator” equations. The Calculator allowed for prediction of an optimal diet characterized by low correlation of PCPI with AADR (Rpredicted) and minimum energy difference from the historical average macronutrient consumption for each corresponding period of life. We predict that protein consumption should be reduced by half in early middle age and late middle age, whereas in late age it should increase. Our predictions are in line with results on humans and simpler organisms in the context of prolonging life.

The Calculator of Anti-Alzheimer's Diet. Macronutrients.

The opinions about optimal proportions of macronutrients in a healthy diet have changed significantly over the last century. At the same time nutritional sciences failed to provide strong evidence backing up any of the variety of views on macronutrient proportions. Herein we present an idea how these proportions can be calculated to find an optimal balance of macronutrients with respect to prevention of Alzheimer’s Disease (AD) and dementia. These calculations are based on our published observation that per capita personal income (PCPI) in the USA correlates with age-adjusted death rates for AD (AADR). We have previously reported that PCPI through the period 1925–2005 correlated with AADR in 2005 in a remarkable, statistically significant oscillatory manner, as shown by changes in the correlation coefficient R (Roriginal). A question thus arises what caused the oscillatory behavior of Roriginal? What historical events in the life of 2005 AD victims had shaped their future with AD? Looking for the answers we found that, considering changes in the per capita availability of macronutrients in the USA in the period 1929–2005, we can mathematically explain the variability of Roriginal for each quarter of a human life. On the basis of multiple regression of Roriginal with regard to the availability of three macronutrients: carbohydrates, total fat, and protein, with or without alcohol, we propose seven equations (referred to as “the calculator” throughout the text) which allow calculating optimal changes in the proportions of macronutrients to reduce the risk of AD for each age group: youth, early middle age, late middle age and late age. The results obtained with the use of “the calculator” are grouped in a table (Table 4) of macronutrient proportions optimal for reducing the risk of AD in each age group through minimizing Rpredicted−i.e., minimizing the strength of correlation between PCPI and future AADR.

Correlation of Alzheimer's disease death rates with historical per capita personal income in the USA.

Alzheimer’s disease (AD) is a progressive degenerating disease of complex etiology. A variety of risk factors contribute to the chance of developing AD. Lifestyle factors, such as physical, mental and social activity, education, and diet all affect the susceptibility to developing AD. These factors are in turn related to the level of personal income. Lower income usually coincides with lower level of education, lesser mental, leisure—social and physical activity, and poorer diet. In the present paper, we have analyzed the correlation of historical (1929–2011) per capita personal income (PCPI) for all states of the USA with corresponding age-adjusted AD death rates (AADR) for years 2000, 2005 and 2008. We found negative correlations in all cases, the highest one (R ≈ -0.65) for the PCPIs in the year 1970 correlated against the AADRs in 2005. From 1929 to 2005 the R value varies in an oscillatory manner, with the strongest correlations in 1929, 1970, 1990 and the weakest in 1950, 1980, 1998. Further analysis indicated that this oscillatory behavior of R is not artificially related to the economic factors but rather to delayed biological consequences associated with personal income. We conclude that the influence of the income level on the AD mortality in 2005 was the highest in the early years of life of the AD victims. Overall, the income had a significant, lifelong, albeit constantly decreasing, influence on the risk of developing AD. We postulate that the susceptibility of a population to late-onset AD (LOAD) is determined to a large extent by the history of income-related modifiable lifestyle risk factors. Among these risk factors, inappropriate diet has a significant contribution.

Tropics and Income in the U.S. States: Further Evidence from Recent Data

Following Andrew Kamarck (Tropics and Economic Development, 1976), Ram (Review of Income and Wealth, 1999) studied the relationship between the degree of tropicality and personal income per capita in the U.S. states over the period 1929– 1990. His estimates indicated that the tropicality disadvantage declined from 1929 to 1970, although the estimate for 1990 does not seem significantly different from that for 1970. The decline from 1929 to 1970 implies that the disadvantage due to location near the tropics is not immutable. Decline in the importance of agriculture, improvements in income and technology, and appropriate public policies can mitigate the adverse effects of tropicality on human health, capital formation, agricultural conditions, and overall productivity. Since the last year studied by Ram was 1990, the issue was revisited here to assess the status of the tropicality disadvantage in recent years. Following Ram (1999), the following simple model of a state’s per-capita personal income was estimated:

Abstracts - 2010 Meetings

Abstracts - 2010 Meetings

Distribution of tourism economic impacts: a longitudinal study

This study assesses the longitudinal economic impact of tourism on the Penghu Islands using an input?output analysis. The objectives of this study are to determine multiplier effects on the local economy, to characterise distributive issues regarding the economic impacts on development stages. The results suggest that certain sectors on the Penghu Islands are more positively influenced than others because of their relationship with tourism. Only those tourism-related sectors (retail trade, food and beverage services, transportation, hotel services and recreation services) receive direct economic benefit. Few non-tourism-related sectors in the economy are positively affected by tourism in both output and per-capita personal income. The longitudinal study finds that the rankings in the two stages are very similar although the average income on each sector in 2003 is lower than that in 1998. The results indicate that tourism industry needs to be developed and integrated into the local economy so that the whole community benefits.

Income convergence in the United States: a tale of migration and urbanization

We use nonparametric distribution dynamics techniques to reassess the convergence of per capita personal income (PCPI) across U.S. states and across metropolitan (metro) and nonmetropolitan (nonmetro) portions of states for the period 1969–2005. The long-run distribution of PCPI is bimodal for both states and metro/nonmetro portions. Furthermore, the high-income mode of the distribution across metro and nonmetro portions corresponds to the single mode of the long-run distribution across metro portions only. These results (polarization or club-convergence) are reversed when weighting by population. The long-run distributions across people are consistent with convergence. Migration and urbanization are the forces behind convergence.

Income Convergence in the United States: A Tale of Migration and Urbanization

We use non-parametric distribution dynamics techniques to reassess the convergence of per capita personal income (PCPI) across U.S. states and across metropolitan and nonmetropolitan portions of states for the period 1969-2005. The long-run distribution of PCPI is bimodal for both states and metro/nonmetro portions. Furthermore, the high income mode of the distribution across metro and nonmetro portions corresponds to the single mode of the long-run distribution across metro portions only. These results (polarization or club-convergence) are reversed when weighting by population. The long run distributions across people are consistent with convergence. Migration and urbanization are the forces behind convergence.

Determinants of variations in state per capita personal income: a panel data approach

This article employs a panel data analysis to examine factors that affect variations in state real per capita personal income (PCPI) by using a panel of 48 contiguous US states over the period 1950–2000. The preferred Panel-Corrected Standard Errors (PCSE) approach reveals that the important explanatory variables are, respectively, the percentage of the population with a college education (COLLEGE), the percentage of the population with a high school education (HIGHSCHOOL), the percentage of the population employed in the manufacturing sector (MANUFACTURING), the percentage of population employed in the service sector (SERVICE) and the percentage of the population that was African American (BLACK). The results are found to be sensitive to estimation technique, suggesting formal model misspecification tests are required in order to choose an approach with better statistical properties.

Convergence in the United States: A Tale of Migration and Urbanization

We use non-parametric distribution dynamics techniques to reassess the convergence of per capita personal income (PCPI) across U.S. states and across metropolitan and nonmetropolitan portions of states for the period 1969-2005. The long-run distribution of PCPI is bimodal for both states and metro/nonmetro portions. Further- more, the high income mode of the distribution across metro and nonmetro portions corresponds to the single mode of the long-run distribution across metro portions only. These results (polarization or club-convergence) are reversed when weighting by population. The long run distributions across people are consistent with convergence. Migration and urbanization are the forces behind convergence.

The Effect of Endogenous Right-to-Work Laws on Business and Economic Conditions in the United States: A Multivariate Approach

A state’s right to prohibit unions from compelling employees to pay dues even when they are covered by a collective bargaining agreement has its basis in the 1947 Taft-Hartley amendments to the National Labor Relations Act (1935). After the amendment's passage, twelve states passed “right-to-work” laws--as did ten more states in the intervening years. Although there has been considerable research on the effect of right-to-work laws on union density, organizing efforts, industrial development and some study of wage differences, there has been little or no examination of the legislation’s influence on business and economic conditions across states. In this paper, the average differences in business conditions, employment, personal income, wages and salaries, and proprietors’ income across states that have enacted right-to-work laws versus those states that did not, are examined assuming that the legislation is endogenous and controlling for state real economic growth, region, and year. Although right-to-work states may be more attractive to business, this does not necessarily translate into enhanced economic verve in the right-to-work state if there is little “trickle-down” from business owners to the non-unionized workers. While the number of self-employed is higher and business bankruptcies lower on average in right-to-work states, there is no significant difference in capital formation or employment rates, ceteris paribus. In addition, per-capita personal income and wages are both lower, yet proprietors’ income is higher in right-to-work states.

Unit root tests of sigma income convergence across us metropolitan areas

The standard deviation of metropolitan per capita personal income (PCPI) and metropolitan average wage per job (AWPJ) provide straightforward indicators of unconditional sigma convergence for metropolitan economies within the United States. Using data for all metropolitan areas in the continental United States for the period 1969–2001, we tested for the unconditional sigma income convergence hypothesis by applying two unit root tests to the time series of the two standard deviations. Our results indicate that the time series can be described as random walks with drift, thereby supporting the claim that income divergence among metropolitan economies is not decreasing.

Are Inequality and Poverty Harmful for Economic Growth: Evidence from the Metropolitan Areas of the United States

This article explores how initial income inequality and poverty are related to subsequent economic growth in the metropolitan statistical areas (MSAs) of the United States. In contradiction to many recent findings based on cross-country regressions, the results of this investigation show a robust positive relationship between initial (1980) MSA income inequality and subsequent MSA per capita personal income (PCPI) growth rate. Initial MSA poverty rate, on the other hand, is negatively associated with MSA PCPI growth rate. But this relationship is not statistically significant in some of the regressions. The results also show that MSAs with higher PCPI growth rates have lower end-of-period poverty and inequality; hence, there may exist a virtuous cycle of poverty reduction and economic growth. A by-product of this study is the compilation of a dataset on MSA income inequality and poverty for the years 1980 and 1990.

PUBLICATION OF PSYCHOLOGICAL RESEARCH AMONG PH.D.-GRANTING INSTITUTIONS: 1952-1961.

The psychological research productivity of Ph.D.-granting institutions over a 10-yr. period was investigated. For the decade 1952-1961, the number of articles published in nine APA journals by individuals at 93 universities was determined. As with individuals, a small proportion of departments contribute a relatively large proportion of the publication output. This index of research productivity correlated significantly with departmental size, average academic salary of the institution, and the productivity of clinical psychologists who were alumni of the institution. When these publication totals were grouped by states, the number of psychological articles published in each state was found to correlate significantly with percentage of population classified as urban, average salaries of classroom teachers in public schools, expenditure for schools per pupil, and per-capita personal income.