Time-series Cross-sectional Models Research Articles

Forest Resources, Government Policy, and Investment Location Decisions of the Forest Products Industry in the Southern United States

Abstract In this article, the results of an initial attempt to estimate the effects of state attributes on plant location and investment expenditure were presented for the forest products industry in the southern United States. A conditional logit model was used to analyze new plant births, and a time-series cross-section model to assess the total capital expenditure. Significant positive effects were found for personal income and forest inventory, and negative effects were found for population density. In the short run, tax and energy costs had negative impacts on new plant births in a state, while in the long run, stumpage price and environmental stringency had negative effects on the capital expenditure. Sensitivity of model specification was documented, and policy implications were discussed. For. Sci. 47(2):169–177.

Relationships between highway capacity and induced vehicle travel

The theory of induced travel demand asserts that increases in highway capacity will induce additional growth in traffic. This can occur through a variety of behavioral mechanisms including mode shifts, route shifts, redistribution of trips, generation of new trips, and long run land use changes that create new trips and longer trips. The objective of this paper is to statistically test whether this effect exists and to empirically derive elasticity relationships between lane miles of road capacity and vehicle miles of travel (VMT). An analysis of US data on lane mileage and VMT by state is conducted. The data are disaggregated by road type (interstates, arterials, and collectors) as well as by urban and rural classifications. Various econometric specifications are tested using a fixed effect cross-sectional time series model and a set of equations by road type (using Zellner’s seemingly unrelated regression). Lane miles are found to generally have a statistically significant relationship with VMT of about 0.3–0.6 in the short run and between 0.7 and 1.0 in the long run. Elasticities are larger for models with more specific road types. A distributed lag model suggests a reasonable long-term lag structure. About 25% of VMT growth is estimated to be due to lane mile additions assuming historical rates of growth in road capacity. The results strongly support the hypothesis that added lane mileage can induce significant additional travel.

Foreign Speculators and Emerging Equity Markets

A number of countries have delayed the opening of their capital markets international investment because of reservations about the impact of foreign speculators on both expected returns and volatility. We propose a cross-sectional time-series model that attempts to assess the impact of liberalizations, in the form of the offering of depositary receipts country funds and other financial instruments, in an extranational and volatility in emerging equity markets. We also examine the impact of capital market liberalizations on the correlation of emerging equity returns and the world return. Our empirical approach designed control for other economic events which might confound the impact of foreign speculators on local equity markets. Whatever the empirical specification the cost of capital always decreases after a capital liberalization but the effect is economically and statistically weak. The effects on volatility and correlation are less robust.

A STATISTICAL ANALYSIS OF INDUCED TRAVEL EFFECTS IN THE U.S. MID-ATLANTIC REGION

The hypothesis of induced travel demand is investigated. County level data from Maryland, Virginia, North Carolina, and Washington, D.C. are used to estimate fixed-effects cross-sectional time series models that relate travel levels, measured as daily vehicle miles of travel, to roadway capacity in lane miles. This includes analysis of a difference (or growth) model estimated using a two-stage least squares procedure with an instrumental variable to account for simultaneity bias. Individual models for each state, a combined-state model, and a model with data from the Washington, D.C./Baltimore metropolitan area are estimated. Average elasticities of vehicle miles of travel (VMT) with respect to lane miles are estimated. The results build on recent research in this area by confirming both the range of elasticities found in other studies and the robustness of these estimates by accounting for simultaneity bias.

The role of foreign capital in domestic manufacturing productivity: empirical evidence from Asian economies

The paper empirically examines the relative contribution of foreign and domestic machinery and equipment on manufacturing productivity in seven Asian economies. A Cobb-Douglas production function is used to test whether foreign machinery is more productive than domestic machinery. The study is based on a pooled cross-sectional time-series model, including seven countries - Hong Kong, Singapore, South Korea, Malaysia, Indonesia, the Philippines and India - for the years 1975 to 1990. The results support the hypothesis that a country's stage of development, skill-level of its labour force, and the technology embodied in capital play a crucial role in determining the relative impact of foreign and domestic capital on manufacturing productivity.

Health Reform in the States:A Model Of State Small Group Health Insurance Market Reforms

For the fourth time since World War II, national policymakers, in 1992, engaged in a major debate over reforming and regulating the U.S. health care system. One of the most debated issues involved the problem of the uninsured. While Congress and the President garnered national attention debating the issue, several states were already dealing with the issue of health insurance and their own uninsurance problems. Today, in the absence of activity at the federal level, the states have become the de facto leaders in health care reform. Since 1990, forty-six states have adopted small group insurance market reforms. Such reforms are designed to improve the availability of insurance coverage for employees of small firms, who make up the largest segment of the uninsured in the states. This article examines the factors that account for the sudden pop ularity of small group insurance market reforms, and the factors or char acteristics of the states that explain the extent of policies adopted. To examine these questions, a pooled cross-sectional time series model is employed. The results indicate the factors contributing to the adoption of small group health insurance market reforms are a state's regulatory envi ronment, a state's regulatory philosophy, state fiscal health, problem severity, and the activities of neighboring states. Implications of the find ings are also discussed.

Comment analyser les données chronologiques pour plan partitionné en sciences sociales

How to Analyze Time-Series Cross-Section Data in the Social Sciences. In this paper we present, step by step, a SAS statistical program for the analysis of Time-Series Cross-Section (TSCS) data which gives robust and unbiased regression estimates. Several statistical packages (SHAZAM. SAS. SPSS) offer procedures for the analysis of TSCS data based entirely, or in part, on a particular application of the Generalized Least Squares (GLS) method developed by Parks and Kmenta. In a series of recent articles. Beck and Katz have shown that the GLS estimation method often underestimates substantially the standard error of regression parameters in TSCS models. They suggest a new method for generating adequate correction of the error process in TSCS models. This method consists of using Ordinary Least Squares (OLS) parameter estimates first. and then replacing OLS standards errors (which are biased) with unbiased Panel-Corrected Standard Errors (PCSEs) obtained after correcting both temporal autocorrelation and spatial correlation structures. The paper provides a SAS application of the method suggested by Beck and Katz. The SAS program can be downloaded through our web site.

Factors affecting the performance of family planning workers: importance of geographical information systems in empirical analysis

An intensive family planning intervention based on community health workers (CHWs) has been in place in the Matlab area of rural Bangladesh for over a decade. Despite the programme's relative success, considerable variations in the performances of CHWs remain a concern. The purpose of this paper is to explore the determinants of CHWs performances by introducing geographical factors in addition to the conventional socioeconomic and other related variables. The attribute data on the study area were obtained from a longitudinal surveillance system, and the spatial data came from a geographical information system (GIS) database. The catchment areas for all 80 CHWs were defined by using GIS technology and spatially referenced data. A cross-sectional time-series regression model was employed on the longitudinal data of 16 years for the 80 CHWs. One significant finding of the empirical analysis is that the size of catchment area influences the performance of CHWs significantly. Geographical barriers to movement in the catchment area also affect performance of the CHW. The exercise implies that the performance of the CHWs can be improved significantly by defining their catchment areas using GIS techniques. Copyright © 1999 John Wiley & Sons, Ltd.

Central Bank Independence and Wage Bargaining Structure - Empirical Evidence

This paper studies the relationship between central bank independence, wage bargaining structure and macroeconomic performance in OECD countries. A cross-sectional time-series (TSCS) model for inflation, nominal wage growth and unemployment for the period 1973-1996 is estimated using different and updated measures of central bank independence. The importance of the price stability objective in the central bank statute is used as a proxy for the degree of conservativeness of the central bank. A recently published data set on wage bargaining structure is used, and a distinction is made between coordination of wage bargaining and formal centralization. A new measure of union power is constructed, which combines formal centralization and union density. The implications of the large differences that can be seen between coverage and unionization rates in some countries are briefly discussed. Two important results emerge. First, the central bank's political independence and personnel independence contribute most importantly to a successful inflation policy. Second, a high level of coordination contributes to moderate inflation rates and unemployment, while union monopoly power tends to increase inflation.

Causal Heterogeneity in Comparative Research: A Bayesian Hierarchical Modelling Approach

Pooled cross-sectional time-series models in comparative politics typically constrain the effects of variables to be identical across countries. These models conflict with general principles of comparative analysis and theories of comparative political economy that the models are designed to test. In contrast, Bayesian hierarchical models allow time-series coefficients to vary across countries, and time-series effects can be related to cross-national variation in institutions. While allowing causal complexity into comparative analysis, the hierarchical model also provides: (1) more accurate forecasts than rival models; (2) more accurate estimates of time-series effects than unpooled analysis; and (3) a more realistic accounting of uncertainty than conventional pooled analysis. In addition, Bayesian theory for the hierarchical model helps specify the concept of comparability in comparative research. These ideas are illustrated in a reanalysis of a model of the political determinants of economic growth studied by Alvarez, Garrett, and Lange (1991).

Comparing absentee and precinct voters: A view over time

This paper examines the trend in absentee voting over the last 30 years in California. With the liberalization of absentee voting laws and practices, an increase in the numbers of absentee voters quickly followed. Absentee voters have already demonstrated their ability to influence the outcomes of local elections. An open question is what will become of absentee voters in the future. If they are the model for “voting at home,” and if technological advances allow such, then the behavior of current absentee voters may be indicative of the future electorate. The increasing trend of voters opting for absentee ballots is analyzed by using GLS on a random-effects time-series cross-section model with county-level data. The focus is on identifying structural factors such as changing voter demographics that have influenced the decision of voters to cast absentee ballots. Thirty-three recent statewide elections in California are the basis for this analysis, covering the statewide primary and general elections from November 1962 through November 1994. We find that the impact of demographics and time trends on absentee voting differ between general and primary elections. In addition, we find that a 1977 liberalization law in California had the effect of accelerating the usage of the absentee format. Finally, we conclude that absentee and precinct voting are substitutes in general elections but complements in primary elections.

Purchasing behaviour of higher-and lower-income shoppers: a look at breakfast cereals

Scanner data for breakfast cereals are used to estimate demand elasticities for six supermarket stores in two distinct socioeconomic areas. Three stores are in lowincome locations and three are in high-income locations. A time series cross-section model is estimated for five product categories across six cross sections over forty-two weeks. Results show lower-income shoppers to have more elastic demands for four of the five product categories: private label cold cereals, the top ten brands of cold cereals, all other brands of cold cereals, and hot cereals. Price is not statistically significant for a fifth product category, snack cereals.

What To Do (and Not to Do) with Time-Series Cross-Section Data

We examine some issues in the estimation of time-series cross-section models, calling into question the conclusions of many published studies, particularly in the field of comparative political economy. We show that the generalized least squares approach of Parks produces standard errors that lead to extreme overconfidence, often underestimating variability by 50% or more. We also provide an alternative estimator of the standard errors that is correct when the error structures show complications found in this type of model. Monte Carlo analysis shows that these “panel-corrected standard errors” perform well. The utility of our approach is demonstrated via a reanalysis of one “social democratic corporatist” model.

Fixed effects with interpersonal and intertemporal covariance

The paper considers the estimation of a fixed effects time series-cross section model where errors have both unspecified interpersonal and intertemporal covariance. Efficient estimators in the form of GLS are suggested, which can be implemented on the data in their actual form or in deviations from time-means. As an empirical example, the determinants of new residential construction activity in the New England states of the US during the 80's are investigated. Results show substantial sensitivity to changes in the interest rate and the unemployment rate, whilst responses to changes in income are more muted. Long term factors related to the region are also influential.

The effect of unemployment insurance on unemployment rate and average duration: evidence from pooled cross-sectional time-series data

This paper empirically analyses the impact of the unemployment insurance system upon the insured unemployment rate and the average duration of unemployment. It employs a simultaneous equation framework because of possible feedback effects between the insured unemployment rate and the average duration of unemployment. Based on a pooled crosssectional time-series model (covering all the 50 states in the USA for the years 1967–88) that corrects for heteroscedasticity and autocorrelation, and the results show some support for the hypothesis that the unemployment insurance system, by providing workers with a safety net, increases both the insured unemployment rate and the duration period.

Foreign direct investments in developing countries: The openness hypothesis and policy implications

A cross-sectional time series model was estimated to explain the influence of the openness of an economy and political instability on gross inflow of foreign direct investments into developing countries. Results indicate positive relation between the openness of developing economies and the inflow of foreign direct investments and negative relation between political instability and the inflow of foreign direct investments. Research findings and policy implications are presented.

Small firm “presence” in Indian manufacturing

This paper employs a pooled cross-section time-series model to examine the determinants of the relative importance of registered small firms in Indian manufacturing. These determinants include both industry-specific and economy-wide characteristics. Small firms perform relatively better in an expansionary macroeconomy and in industries with less vertical integration and economies of scale in management, and where small firms are able to overcome their inherent cost disadvantages. The evidence suggests the more capital intensive the industry, the greater small firm presence.

The influence of socioeconomic and technological factors on direct mail volume in western european economies: A Pooled Cross-Sectional Time-Series Analysis

This article discusses the influence of socioeconomic and technological factors on direct mail volume in 12 Western European economies. Relations between these variables are studied using a pooled cross-sectional time-series model. The findings suggest that telephones and income significantly influence direct mail volume in these Western European economies. Research hypotheses, empirical findings, and future research directions are presented.

Class Context and Pension Response to Demographic Structure in Advanced Industrial Democracies

This paper readdresses debates over the competing influence of class power and size of the aged population on pension spending by considering how the corporatist/pluralist dimension of interest representation shapes the effects of age and class. Corporatism, taken as the degree to which officially-designated representatives of class groups are integrated within and organized by the state for mediation in national policy formation, provides the context in which age and class mobilization may influence pension spending. After measuring the degree of corporatism for 18 advanced industrial democracies, we estimate pooled time-series cross-section models for the period 1959-1980 in which dynamic determinants of pension spending vary with corporatist context. The results support the theoretical predictions that (1) the positive effects of age structure on pension spending are diminished by corporatism (and increased with pluralism) and (2) the effect of class variables such as partisan party rule and business profits are increased by corporatism (and decreased by pluralism). This suggests theoretical integration of diverse explanations of pension spending by specifying the context in which each best applies.

Sclerosis, Convergence, and Taxes: Determinants of Growth among the US States

Three theories of economic growth are investigated using data for the US states. They are the ‘sclerosis' theory that redistributive coalitions slow growth, the ‘convergence’ theory which predicts faster growth in low-income economies, and the ‘supply-side’ theory emphasizing the disincentive effects of taxation. Simultaneous testing of these theories requires the use of a pooled cross-section time-series model which allows temporal variation in measures of income growth, sclerosis, and taxes. Each theory has some empirical support for the period 1961–84.