Highway Infrastructure Investment and Regional Employment Growth: Dynamic Panel Regression Analysis

A number of macro-level studies attempting to establish the statistical link between public investment in highway infrastructure and employment have applied econometric techniques to estimate the effect of highways while controlling for the effects associated with other factors. Unfortunately, direct use of empirical findings from these historic and recent studies, in shaping transport policy and supporting particular investment decisions, has been rather limited by mixed and inconclusive evidence in the literature. Apart from the common differences among these studies in scope and methodology, another possible reason for the contradictory evidence is that much of the previous work has generally suffered from several methodology drawbacks. In many studies, for instance, several important determinants of employment growth are omitted, and the choices of control variables included in the estimated equations generally are not based on theory. Those studies based solely on cross-sectional data also typically do not account for unobserved regional heterogeneity that may explain spatial differences in employment changes. Moreover, the possibility that the causal relationship between transportation investment and economic growth could work in both directions is generally ignored. This paper attempts to shed some light on this controversy by analysing the effect of highway investment on county-level employment in the State of North Carolina, United States. We derive a reduced from model of equilibrium employment that considers the effects of highways and other potential factors on the supply and demand for labour. Given the potential for lagged responses of the labour market to any exogenous shock, we assume a partial adjustment process for actual employment in our empirical model. A panel data set for 100 North Carolina counties from 1985 to 1997 is used in order to control for unobserved county and time specific effects using panel regression techniques. We also address the causality issue by the use of a two-stage least squares procedure with an instrumental variable. Our main results are that the employment effect of highway infrastructure depends critically on model specifications considered, and failure to account for the dynamics of employment adjustment could lead to an upward bias in the estimated effect of highways.

Appraising fiscal reaction functions

We estimate fiscal responses for an OECD panel, accounting for cross-country interactions, and also estimate the fiscal responses in a panel VAR. We find that governments have increased primary balances when facing higher government indebtedness, implying a Ricardian fiscal regime, while primary balances have improved to reduce government debt. These results hold for the single regression panel analysis and for the panel VAR.fiscal regimes, Panel VAR, cross-sectional dependence

A Practical Introduction to Stata

This document provides an introduction to the use of Stata. It is designed to be an overview rather than a comprehensive guide, aimed at covering the basic tools necessary for econometric analysis. Topics covered include data management, graphing, regression analysis, binary outcomes, ordered and multinominal regression, time series and panel data. Stata commands are shown in the context of practical examples.Stata, econometric analysis, data management, regression analysis, graphing, binary outcomes

Appraising fiscal reaction functions

We estimate fiscal responses for an OECD panel, accounting for cross-country interactions, and also estimate the fiscal responses in a panel VAR. We find that governments have increased primary balances when facing higher government indebtedness, implying a Ricardian fiscal regime, while primary balances have improved to reduce government debt. These results hold for the single regression panel analysis and for the panel VAR.fiscal regimes, Panel VAR, cross-sectional dependence Classification-C23, E62, H62

Analysis of interactive fixed effects dynamic linear panel regression with measurement error

This paper studies a simple dynamic panel linear regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method.

PENGARUH NET EKSPOR, INVESTASI DAN EFEKTIVITAS BELANJA PEMERINTAH DAERAH TERHADAP PERTUMBUHAN EKONOMI DI INDONESIA TAHUN 2015-2020

This study aims to find out how the effect of net exports, investment, and regional spending on economic growth in Indonesia in the 2015-2020 period. This type of research is descriptive quantitative using secondary data. This study uses panel data regression analysis. The analysis was carried out using Microsoft Excel 2013 and Stata 14 programs. The analytical tests used were the classical assumption test, panel data regression, and hypothesis testing. Based on the classical assumption test results, the research data meets the requirements to use the panel data regression equation model. The study’s results through the t-test show that the variables of net exports, investment, and regional spending partially have a positive and significant effect on economic growth. The results of the F test showed that the independent variables, namely net exports, investment, and regional spending simultaneously or jointly have a significant effect on economic growth in 34 Indonesian Provinces in the 2015-2020 period. The determination test (R2) results of economic growth in Indonesia are 0.9281 or 92.81%. This can show the relationship of the independent variables, namely net exports, investment, regional spending can explain the dependent variable economic growth of 92.81% while the remaining 7.19% can be explained by other variables

Changes in taxation and their impact on economic growth in the European Union.

The aim of the paper is to analyze changes in taxation and their impact on economic growth in the European Union. The analysis is performed on adjusted annual panel data of 24 European Union countries in a period 1995–2008. Panel regression with fixed effects is used as a basic method of research. The panel regression is based on analysis the effect of total tax quota changes on GDP growth in model 1, of changes in its components (social contribution, direct and indirect tax quotas) in model 2 and of personal and corporate income tax quota changes in model 3. Results of empirical tests verify statistically significant negative effect of tax burden on GDP growth. Total tax quota increased by 1% decreases the GDP growth rate by 0.29% in the same year. Estimations confirm a statistically significant negative effect of direct taxes on GDP growth as well. A cut in the direct tax quota by 1% raises the GDP growth rate by 0.43%. The model also presents a high negative impact of an increase in the corporate income tax quota on GDP growth (a value of the regression coefficient is minus 1.28%) expresses the high negative. The effect of social contribution quota on GDP growth is not statistically significant in any estimation.taxation; tax burden; economic growth; panel regression

Does Social Capital Have a Role in Environmental Kuznets Curve? Spatial Panel Regression Approach

We advance a case for an inclusion of social capital in the environmental Kuznets curve analysis using highly disaggregated data on water pollution in Louisiana. A social capital index and other variables are used in parametric and spatial panel regression models to explain water pollution dynamics.social capital, principal component analysis, environmental Kuznets curve, spatial regression, Environmental Economics and Policy,

3-Step Analysis of Public Finances Sustainability: the Case of the European Union*

We use a 3-step analysis to assess the sustainability of public finances in the EU27. Firstly, we perform the SURADF specific panel unit root test to investigate the meanreverting behaviour of general government expenditures and revenues ratios. Secondly, we apply the bootstrap panel cointegration techniques that account for the time series and cross-sectional dependencies of the regression error. Thirdly, we check for a structural long-run equation between general government expenditures and revenues via SUR analysis. While results imply that public finances were not unsustainable for the EU panel, fiscal sustainability is an issue in most countries, with a below unit estimated coefficient of expenditure in the cointegration relation.fiscal sustainability, EU, panel cointegration.

The Heterogeneity of Convergence in Transition Countries

For two groups of post-communist countries (CEE and CIS) we estimated the parameters of convergence equations on the basis of annual data. We depart from standard econometric theory, which involves panel regression techniques. We test cross-country heterogeneity of parameters within a system of Seemingly Unrelated Regression Equations (SURE). We show empirical evidence in favour of the variability of parameters describing the convergence effect and productivity growth rates across countries. Our approach seems a convincing alternative to the panel regression approach where random effects can be estimated, imposing an assumption about the constancy of structural parameters within the group of countries under analysis. We discuss the role of the global financial crisis in the heterogeneity of convergence processes and productivity at the country level. The aforementioned SURE model was estimated based on two datasets, one containing observations prior to the crisis and the second containing the whole sample.This research was financed by National Science Centre, Poland (decision DEC-2016/21/B/HS4/01565