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

2008 ◽  
Vol 17 (3) ◽  
pp. 235-239 ◽  
Author(s):  
Yihua Yu
Keyword(s):  
Panel Data ◽  
Personal Income ◽  
Per Capita ◽  
Capita Personal Income

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

2020 ◽  
Vol 05 (1&2) ◽  
pp. 1-13
Author(s):  
Mohamed R Abonazel ◽  
Keyword(s):  
Panel Data ◽  
Personal Income ◽  
Spatial Weights ◽  
Spatial Panel Data Models ◽  
Spatial Weights Matrix ◽  
Spatial Panel Data ◽  
Spatial Autoregressive ◽  
Per Capita ◽  
Capita Personal Income ◽  
Inverse Distance

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.

Publication of Psychological Research among Ph.D.-Granting Institutions: 1952–1961

1965 ◽  
Vol 20 (1) ◽  
pp. 87-95 ◽  
Author(s):  
Carole Golightly ◽  
Donn Byrne ◽  
E. J. Capaldi
Keyword(s):  
Public Schools ◽  
Small Proportion ◽  
Research Productivity ◽  
Publication Output ◽  
Psychological Research ◽  
Personal Income ◽  
Classroom Teachers ◽  
Academic Salary ◽  
Per Capita ◽  
Capita Personal Income

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.

An empirical note on entrepreneurship and unemployment

2016 ◽  
Vol 5 (1) ◽  
pp. 73-81 ◽  
Author(s):  
Nicholas Apergis ◽  
James E Payne
Keyword(s):  
Error Correction ◽  
Panel Cointegration ◽  
Personal Income ◽  
Entrepreneurial Activity ◽  
Cross Sectional ◽  
Content Type ◽  
Long Run ◽  
Short Run ◽  
Per Capita ◽  
Capita Personal Income

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.

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

2014 ◽  
Vol 12 (3) ◽  
pp. 257
Author(s):  
Oi Lin Cheung
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Personal Income ◽  
Economic Dynamics ◽  
Per Capita Gdp ◽  
Real Gdp ◽  
Innovative Environment ◽  
Per Capita ◽  
Capita 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>

scholarly journals Is Real Per Capita State Personal Income Stationary? New Nonlinear, Asymmetric Panel-Data Evidence

2015 ◽  
Author(s):  
Furkan Emirmahmutoglu ◽  
Rangan Gupta ◽  
Stephen M. Miller ◽  
Tolga Omay
Keyword(s):  
Panel Data ◽  
Personal Income ◽  
Per Capita

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

2019 ◽  
Keyword(s):  
Confidence Interval ◽  
Capital Expenditure ◽  
Personal Income ◽  
Financial Capacity ◽  
Income Per Capita ◽  
Self Sufficiency ◽  
Development Expenditure ◽  
Per Capita ◽  
Main Determinants ◽  
Capita Personal Income

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.

scholarly journals Is real per capita state personal income stationary? New nonlinear, asymmetric panel‐data evidence

2019 ◽  
Vol 72 (1) ◽  
pp. 50-62 ◽  
Author(s):  
Furkan Emirmahmutoglu ◽  
Rangan Gupta ◽  
Stephen M. Miller ◽  
Tolga Omay
Keyword(s):  
Panel Data ◽  
Personal Income ◽  
Per Capita
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