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.

Proportions of macronutrients, including specific dietary fats, in prospective anti-Alzheimer’s 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.

Do Targeted Business Subsidies Improve Income and Reduce Poverty? A Synthetic Control Approach

Interstate competition for economic development has led many states to adopt targeted economic development incentive programs known as deal-closing funds. Deal-closing funds allow state officials to provide discretionary cash grants to select businesses to attract and retain economic development projects. However, whether these targeted business subsidies increase prosperity in the local economy remains unclear. The authors use evidence from Arkansas’s Quick Action Closing Fund to analyze how effective deal-closing funds are at increasing incomes and decreasing poverty. Specifically, the causal effects of the Quick Action Closing Fund on Arkansas’s county-level per capita personal income and poverty rates are estimated using a synthetic control approach. The results largely suggest that the business subsidy program fails to increase incomes and lower poverty rates over the long term, at least at the county level. These findings should serve as a caution to policy makers who wish to improve incomes and poverty rates with targeted business subsidies.

Capacity of reforms efficiency of administrative and territorial structure (the case of Zaporizhzhia region)

The aim of the article is to examine efficiency of the decentralization process` potential and the conditions for the formation of financially capable and self-sufficient united territorial communities (UTCs) on the basis of sustainable development of territories and national economy alike. Main material. Efficiency of the decentralization process in Zaporizhzhia region has been analyzed in the article. The methodology of UTCs clustering by the level of their financial capacity applying statistical indicators of relative frequency and frequency with the subsequent determination of the confidence interval for mean observations (with probability of 0.95) has been proposed. The following have been chosen as the clustering criteria: income per capita; personal income per capita; infrastructure grant per capita and development expenditure (capital expenditure) per capita. Each set was divided into three groups: the first group of UTCs is from the minimum value to the lower limit of the confidence interval; the second group of UTCs is within the confidence interval; the third group of UTCs is above the upper limit of the confidence interval. It has been found out that the main determinants of UTCs formation of financial capacity and self-sufficiency are the following: natural-geographical (land, forest, water, mineral, biological, energy) and socio-economic (material, financial, human and intangible) resources. Econometric modeling of financial capacity level of UTCs in Zaporizhzhia region has been conducted. Conclusions and further research. The methodology of UTCs clustering by the level of their financial capacity according to the following criteria has been proposed: income per capita; personal income per capita; infrastructure grant per capita and development expenditure (capital expenditure) per capita. It has been used to evaluate efficiency of the decentralization process in Zaporizhzhia region. The main determinants of UTCs financial capacity and self-sufficiency formation has been proved. Regression econometric models have been built to evaluate its development potential and forecasting for UTCs of Zaporizhzhia region. The authors have proved that nowadays there are territories facing the process of UTCs formation. It has been demonstrated in the study that the complex potential of territorial development, namely, natural and socio-economic potentials, should be the basis for the further UTCs formation. The gradients (as the territorially defined set of opportunities) of the complex development potential will form UTCs administrative delimitation (territorial coverage). UTCs will have characteristics like economic capacity and efficient development based on the resources`, interests` and competitiveness` harmony. It has been proved that in the further process of decentralization it is advantageous to carry out UTCs clustering. UTCs should become clusters` centers of gravity (clusters` cores) as they have reached satisfactory financial capacity and selfsufficiency at the voluntary stage of decentralization.

A Fiscally Based Scale for Tropical Cyclone Storm Surge

Categorization of storm surge with the Saffir–Simpson hurricane scale has been a useful means of communicating potential impacts for decades. However, storm surge was removed from this scale following Hurricane Katrina (2005), leaving no scale-based method for storm surge risk communication despite its significant impacts on life and property. This study seeks to create a new, theoretical storm surge scale based on fiscal damage for effective risk analysis. Advanced Circulation model simulation output data of maximum water height and velocity were obtained for four storms: Hurricane Katrina, Hurricane Gustav, Hurricane Ike, and Superstorm Sandy. Four countywide fiscal loss methods were then considered. The first three use National Centers for Environmental Information Storm Events Database (SED) property damages and Bureau of Economic Analysis (BEA) population, per capita personal income, or total income. The fourth uses National Flood Insurance Program total insured coverage and paid claims. Initial correlations indicated the statistical mode of storm surge data above the 90th percentile was most skillful; this metric was therefore chosen to represent countywide storm surge. Multiple linear regression assessed the most skillful combination of storm surge variables (height and velocity) and fiscal loss method (SED property damages and BEA population, i.e., loss per capita), and defined the proposed scale, named the Kuykendall scale. Comparison with the four storms’ actual losses shows skillful performance, notably a 20% skill increase over surge height-only approaches. The Kuykendall scale demonstrates promise for skillful future storm surge risk assessment in the analytical, academic, and operational domains.

A Novel Look at Long-run Convergence Dynamics in the United States

When regional disparities follow a cyclical short-run pattern, convergence analysis results can be sizably distorted. To tackle this issue, we propose a method based on the extraction of the trend from regional income time series that eschews misleading results when the nature of the cyclical pattern changes over time. Using real per capita personal income data for forty-eight conterminous US states and the distribution dynamics approach, we identify the following three distinct consecutive phases: strong convergence (1930–1970), substantial persistence (1971–1980), and divergence (1981–2010).

An empirical note on entrepreneurship and unemployment

Purpose – The purpose of this paper is to extend the existing literature on the causal dynamics between entrepreneurship and the unemployment rate (UR) in the use of the Kauffman Foundation index of entrepreneurial activity. Design/methodology/approach – Recently developed panel unit root tests with recognition of cross-sectional dependence and panel cointegration/error correction modeling techniques are applied to US States. Findings – The results indicate that the rate of entrepreneurship, the UR, and real per capita personal income are cointegrated. The panel error correction model reveals that bidirectional causality exists among the variables in both the short run and long run. With respect to entrepreneurship, an increase in the UR increases the rate of entrepreneurship, in turn, an increase in the rate of entrepreneurship lowers the UR. Moreover, the results also show a positive bidirectional relationship between the rate of entrepreneurship and real per capita personal income. Originality/value – Unlike other standard measures of entrepreneurship, this is the first empirical study of the causal dynamics between entrepreneurship and the UR using the Kauffman Foundation index of entrepreneurial activity.

THE DYNAMIC RELATIONSHIP BETWEEN HOUSE PRICES AND OUTPUT: EVIDENCE FROM US METROPOLITAN AREAS

This paper investigates the long-run and short-term dynamics of 351 US metropolitan statistical area housing prices in relation to personal income. We apply a panel cointegration approach on annual data from 1993 to 2011 and find a long-run relationship between local house prices and per capita personal income. The causal direction is then assessed based on an autoregressive distributed lag specification that also accommodates for error-correction. Results from Granger-causality tests reveal the existence of a bi-directional causality between real house prices and real per capita personal income over both long and short-horizons. Our results continue to be robust, when our bivariate system is extended to include additional MSA-level (employment and population) and national-level variables (real stock price and mortgage interest rate). We conclude that changes in personal income can predict house price movements and vice versa.

Impact Of Innovative Environment On Economic Growth: An Examination Of State Per Capita GDP And Personal Income

<p>This study investigates how the overall innovative environment will affect the economic growth of a place, in particular, a state. Using the Innovation Index and its component indexes as a measure of the innovative environment prevailing in the states, it is found that the more innovative a state is, the higher its per capita real GDP and per capita personal income are. These relations are statistically significant. The higher per capita personal income is associated with both the availability of human capital for innovative activities and the presence of the economic dynamics that facilitate those activities. At the same time, the higher per capita real GDP has been brought about by the availability of such human capital only.</p>