Cross-sectional Time-series Data Research Articles

A Comparative Study of the Effects of Institutional Arrangements in Municipal Solid Waste Services in Korea

In Korea, local governments are primarily responsible for providing municipal solid waste services to citizens. This paper examines the effects of different institutional arrangements and characteristics on cost savings, efficiency gains and productivity in the delivery of municipal solid waste services to citizens. In order to carry out this research, a hybrid cost function approach was employed, and cross-sectional time-series data from local governments of Korea covering a ten-year period (2000–2009) were used for empirical analysis. Empirical findings indicated that there were no effects of contracting-out on cost savings, efficiency and productivity gains in Korea. Specifically, the solid waste service costs were not significantly lower under contracting-out than under direct public delivery. In addition, contrary to the arguments of the proponents of privatization or contracting-out, efficiency and productivity gains were actually higher under direct public delivery than when contracted out.

Who commits to the rule of law? Constrained government and foreign direct investment in postcommunist states

Research linking credible commitments to the rule of law in terms of property rights and contract enforcement is a hallmark of recent efforts to explain economic growth and development. However, many postcommunist states have had difficulty making such commitments and spurring growth. Many argue political polarization prevents states from reforming laws and protecting property rights in some countries whereas single-party governance renders state promises incredible in others. I analyze pooled cross-sectional time-series data for twenty-four postcommunist countries and provide evidence effective constraints among elected officials act as democratic commitment mechanisms rendering government policies credible.

Implementation and Operational Research: Effect of Universal Access to Antiretroviral Therapy on HIV/AIDS Mortality in Mexico 1990-2011.

Universal coverage of highly active antiretroviral therapy (HAART) for HIV/AIDS in Mexico was achieved in a staggered fashion. First, HAART was made available in 1997 for employees in the formal sector and subsequently, in 2003, for informal sector workers and the unemployed population. We evaluated the impact of this free universal HAART program on HIV/AIDS mortality in the Mexican population aged 15 years or older. Time-series cross-sectional data analysis of standardized HIV/AIDS mortality rates (1990-2011) using marginal linear models with inflection points at 1994, 1997, and 2003. Men employed in the formal sector experienced the greatest effect of access to HAART, with a 32% reduction in mortality from 1997 to 2011 (P < 0.01). For men in this sector, mortality increased from 1990 to 2003, then stabilizing at 7 deaths per 100,000. For women in the informal sector, mortality increased from 1990 to 2011. We found large between-state variability: mortality decreased by 59% in Mexico City while it increased by 245% in Tabasco during the study period. Six of 32 states achieved statistically significant reductions in mortality while 5 states continued to experience increasing mortality rates despite universal HAART. Access to universal HAART has had relative success in Mexico. The heterogeneity of HIV/AIDS mortality by employment status, gender, and state of residence highlight urgent needs to improve health equity with pro-poor and gender-responsive programs and a call for country-specific operational research in HIV/AIDS prevention and treatment. Our results may apply to other countries seeking to implement universal access to antiretroviral therapy.

Models for Pooled Time-Series Cross-Section Data

Several models are available for the analysis of pooled time-series cross-section (TSCS) data, defined as “repeated observations on fixed units” (Beck and Katz 1995). In this paper, we run the following models: (1) a completely pooled model, (2) fixed effects models, and (3) multi-level/hierarchical linear models. To illustrate these models, we use a Generalized Least Squares (GLS) estimator with cross-section weights and panel-corrected standard errors (with EViews 8) on the cross-national homicide trends data of forty countries from 1950 to 2005, which we source from published research (Messner et al. 2011). We describe and discuss the similarities and differences between the models, and what information each can contribute to help answer substantive research questions. We conclude with a discussion of how the models we present may help to mitigate validity threats inherent in pooled time-series cross-section data analysis.

Child soldiers as time bombs? Adolescents’ participation in rebel groups and the recurrence of armed conflict

The existent work on child soldiering began only recently to systematically study its consequences, both theoretically and empirically. The following article seeks to contribute to this by examining the impact of rebels’ child soldier recruitment practices during war on the risk of armed conflict recurrence in post-conflict societies. We argue that child soldiering in a previous dispute may increase both the willingness and opportunity to resume fighting in the post-conflict period, while disarmament, demobilization and reintegration programmes could decrease these aspects of conflict recurrence. Empirically, we analyse time-series cross-section data on post-conflict country-years between 1989 and 2005. The findings highlight that the risk of conflict recurrence does, indeed, increase with child soldiers who fought in an earlier dispute, but — counter-intuitively — is unlikely to be affected by the presence of disarmament, demobilization and reintegration programmes in post-conflict societies. This research has important implications for the study of armed conflicts, child soldiering and research on post-conflict stability.

Easy Credit as Social Safety Net? How Interest Rate Changes Affect US Social Policies.

Access to credit not only enables people to consume beyond their current income, but also increasingly determines life chances and access to basic social services. This paper argues that there is a trade-off between private credit and the welfare state and proposes a causal model of social policy-making where policymakers incorporate the availability of credit in their considerations of how to distribute welfare resources. Drawing on time-series cross-sectional data from US States I first show that a decline in the share of denied mortgages is associated with lower health care and unemployment expenditures and a modest decline in unemployment insurance generosity. Secondly, I exploit exogenous variation in state-level mortgage interest rates induced by differential timing in bank branch deregulation to demonstrate that improved access to mortgage credit similarly decreases state-level health care and unemployment expenditures and unemployment insurance generosity. The findings of this paper provide causal evidence that easier access to credit lowers state-level public health and unemployment expenditures. These credit flow to families enabled policymakers to shift the burden of social policies from the domain of the publicly financed welfare state into the domain of privately-funded market-driven welfare state. The transition toward a credit-based welfare state has broad socioeconomic consequences. Credit can serve as an alternative form of or substitute for social redistribution and social insurance, but it cannot replace it because the distributional and stratifying implications are not the same as in the case of publicly provided social policies.

Incidence and prevalence of pediatric onset multiple sclerosis in Kuwait: 1994–2013

ObjectivesThis study aimed to assess the incidence and prevalence of pediatric-onset multiple sclerosis (POMS) along with temporal and gender differentials in these estimates in Kuwait. MethodsWe identified MS patients with pediatric (age <18years) onset between 1994 and 2013 from national MS registry. Year and gender-specific incidence rate and prevalence estimates were computed. Multivariable Poisson regression analyses of time-series cross-sectional panel data were conducted to evaluate temporal and gender related variations in yearly POMS incidence rate and prevalence. Results122 POMS patients were identified; of which 90 (73.8%) were females. During 2013, POMS incidence rate and prevalence (per 100,000) were 2.1 and 6.0 respectively. Multivariable Poisson regression model revealed statistically significant 5% increase in POMS incidence rate (p=0.002) and 6% increase in prevalence (p<0.001) from 1994 to 2013. Furthermore, during the study period, female children were more likely to have higher POMS incidence rate (relative rate=2.9; p<0.001) and prevalence (prevalence ratio=2.8; p<0.001). ConclusionsThe temporal increase and gender disparity in POMS incidence and prevalence corroborate the findings of earlier studies conducted elsewhere. Knowledge of increasing POMS burden may help in optimal planning for better management of patients in the region.

Causes and Incentives for Terrorism in Pakistan

This study offers fresh empirical insights into the causes of terrorism in Pakistan. The authors present a novel strategy for hypothesis building in conflict studies, and explore the importance of the explanatory variables within the time frame of the analysis. The hypothesized relationships are tested using pooled cross-section time series data from five regions of Pakistan (the federally controlled area and four provinces from 1980 to 2010) using fixed effect negative binomial regression. The results indicate that public education expenditures, law & order expenditures, ethnic diversity, urban population, the presence of domestic military operations, and U.S. military aid to Pakistan all result in increased terrorist activity in Pakistan. This study recommends that ethnic diversity and multilingualism be respected in education in Pakistan, that the educational curriculum be cleansed of systemic incendiary language and bigotry, that law enforcement agencies be freed of political control, and that strategic partnership with the United States be reassessed considering the core long-term interests of Pakistan.

Projections of potential flows to the enlarging EU from Ukraine, Croatia and other Eastern neighbors

AbstractThis study evaluates potential migration flows to the European Union from its Eastern neighbors and Croatia. We perform out-of-sample forecasts to time series cross-sectional data about post-enlargement migration flows following the EU’s 2004 enlargement. We consider two baseline policy scenarios, with and without accession of sending countries to the EU. Our results show that migration flows are driven by migration costs and economic conditions, but the largest effects accrue to policy variables. In terms of the predicted flows: (i) we can expect modest migration flows in the case of no liberalization of labor markets and only moderately increased migration flows under liberalization; (ii) after an initial increase following liberalization, migration flows will subside to a long run steady state; (iii) Ukraine will send the most migrants; and (iv) the largest inflows in absolute terms are predicted for Germany, Italy and Austria, whereas Ireland, Denmark, Finland and again Austria are the main receiving countries relative to their population.

Generalized Synthetic Control Method for Causal Inference with Time-Series Cross-Sectional Data

Difference-in-differences (DID) is commonly used for causal inference in time-series cross-section data. It requires the assumption that the average outcomes of treated and control units would have followed parallel paths in the absence of treatment. In this paper, I propose a method that not only relaxes this often-violated assumption, but also unifies the synthetic control method (Abadie, Diamond and Hainmueller, 2010) with linear fixed effect models under a simple framework, of which DID is a special case. It imputes counterfactuals for each treated unit using control group information based on a linear interactive fixed effect model that incorporates unit-specific intercepts interacted with time-varying coefficients. This method has several advantages. First, it allows the treatment to be correlated with unobserved unit and time heterogeneities under reasonable modelling assumptions. Second, it generalizes the synthetic control method to the case of multiple treated units and variable treatment periods, and improves efficiency and interpretability. Third, with a built-in cross-validation procedure, it avoids specification searches and thus is easy to implement. An empirical example of Election Day Registration and voter turnout in the United States is provided.

Modeling Crash Rates for a Mountainous Highway by Using Refined-Scale Panel Data

Traditional traffic safety analyses on crash frequency or crash rate usually focus on highly aggregated cross-sectional data. The adoption of aggregated data ignores the time-varying nature of some critical factors, and their effects on traffic safety may be masked through data aggregation. For mountainous highways, weather- and environment-related variables become critical as a result of complex time- and spatial-varying characteristics as well as interactions with mountainous terrain. Therefore, refined-scale models are often desired to appropriately model crash safety risks on mountainous highways and disclose the inherent crash mechanism. An advanced random parameter Tobit model with panel data (time series cross-sectional data) in refined temporal scale was developed. This is so far the first reported effort on integrating random parameter Tobit model and refined-scale panel data to develop crash rate models. A random parameter model was adopted not only to handle unobserved heterogeneity explicitly, but also to account for serial correlations across observations in panel data. Refined-scale weather and traffic data in a panel formation were adopted to accommodate the varying nature of complex driving conditions. Interstate 70 (I-70) in Colorado is well known for its typical mountainous terrain, critical role for local and national traffic, and inclement weather. As a demonstration of the modeling techniques, crash rates for a segment of I-70 were investigated in refined temporal scale. Results showed that a random parameter Tobit model outperformed a fixed-parameter Tobit model, and factors related to traffic, weather, and surface conditions were found to play significant roles in an accident rate model.

The Relationship between Income, Consumption and GDP: A Time Series, Cross-Country Analysis

This paper attempts to investigate the co-integration relationship between consumption, income and GDP per capita (as a proxy of the level of standard of living) in time-series cross-section data. To conduct this analysis, we have applied tests to verify if the time series are non-stationary and co-integrated. The panel data covers a large sample formed from 79 countries, divided in three categories depending on their income level – low, middle and high. The study regarded annual observations for a period of 31 years, from 1980 to 2010. The results have shown that the association between consumption and income is stronger in low and high income countries, compared with middle income countries. A small level of income determines its use especially for consumption and a high level of income increases consumption as there are more available resources to cover large investments as well. The relation between consumption, income and GDP is stronger for low and middle income countries, a logical conclusion since the high income countries allocate more capital to investments and are intense specialized in research and development activities.

Comparison of Uniform and Kernel Gaussian Weight Matrix in Generalized Spatial Panel Data Model

Panel data combine cross-section data and time series data. If the cross-section is locations, there is a need to check the correlation among locations. ρ and λ are parameters in generalized spatial model to cover effect of correlation between locations. Value of ρ or λ will influence the goodness of fit model, so it is important to make parameter estimation. The effect of another location is covered by making contiguity matrix until it gets spatial weighted matrix (W). There are some types of W—uniform W, binary W, kernel Gaussian W and some W from real case of economics condition or transportation condition from locations. This study is aimed to compare uniform W and kernel Gaussian W in spatial panel data model using RMSE value. The result of analysis showed that uniform weight had RMSE value less than kernel Gaussian model. Uniform W had stabil value for all the combinations.

The Impact of Institutional Coup-Proofing on Coup Attempts and Coup Outcomes

Coup-proofing pertains to political leaders’ strategies that will prevent groups inside or outside the state apparatus from seizing power via a coup d’état. One particular form of these strategies divides a country’s military into rivaling organizations, thereby creating an artificial balance between and structural obstacles for the armed forces. Despite the general claim that this institutional coup-proofing is indeed effective, a recent empirical study does not obtain evidence for a negative impact on the risk of coup attempts or coup outcomes. The authors take this finding as a motivation for their re-evaluation of the effect of institutional coup-proofing on coup risk and outcomes. By developing an argument that rests on the concepts of collective action and polarization, it is contended that institutional coup-proofing and coups are characterized by a U-shaped relationship: Institutional coup-proofing is likely to lower the likelihood of coup onsets and successful outcomes, yet only until a tipping point of about two equally strong military organizations. After this turning point, the risk of coup onset as well as coup success may increase again. Using time-series cross-section data for 1975–1999, the authors find strong and robust support for their claims in terms of coup onset, but not coup outcomes.

Lingua Mercatoria: Language and Foreign Direct Investment

Does language choice attract foreign direct investment (FDI), and if so, how? We argue that language—a dynamic instrument for reducing transaction costs—can influence investors' decision to allocate capital. Potential host countries attract investments by coordinating their domestic language policies—especially those in education—to match the language of the potential FDI investor. We subject our argument to three different tests: (i) a cross-sectional sample of all global Organization for Economic Co-operation and Development investments that employs a newly constructed language-in-education measurement; (ii) a newly assembled time-series cross-sectional data set of all Chinese FDI abroad; and (iii) a detailed case study that uses process tracing to explain Chinese FDI in Indonesia. The results from these tests demonstrate a significant and robust relationship between language and FDI.

Inequality, Economic Growth and Poverty in the Middle East and North Africa (MENA)

In this paper, we have presented the patterns of inequality, growth and income inequality in the MENA region. Using a cross-sectional time series data of MENA countries for the period 1985–2009, we have also investigated the effect of income inequality on key societal development, namely economic growth and poverty, in the region. Our empirical results show that income inequality reduces economic growth and increases poverty in the region. Other factors having significant negative effect on economic growth in the MENA region include previous growth rate, exchange rate, government consumption expenditure or government burden, initial per capita GDP, inflation and primary education. On the other hand, variables positively and significantly associated with MENA's economic growth are domestic investment rate, urbanization, infrastructure development, and mineral rent as a percentage of GDP. In addition, apart from income inequality, other factors increasing poverty in the region are foreign direct investment, population growth, inflation rate, and the attainment of only primary education. Poverty-reducing variables in the region include domestic investment, trade openness, exchange rate, income per capita, and oil rents as a percentage of GDP.

Korean Bilateral Official Development Assistance to Africa Under Korea's Initiative for Africa's Development

In the past several years, the Republic of Korea—a former least developed country (LDC) and aid recipient that became a donor—joined the “club of emerging donors” to Africa. In March 2006, President Roh Moohyun declared Korea's Initiative for Africa's Development. The initiative puts poverty reduction and socioeconomic development of African countries in the forefront. Using pooled cross-sectional time series data, in this study we examine the determinants of Korean bilateral official development assistance (ODA) to Africa for the period 1991–2011. The findings of the study suggest that the approach of Korean ODA does not differ significantly from that of many conventional donors whose ODA disbursement has had a dual purpose: to improve the welfare of developing countries and to serve self-interests.

How NGOs Influence US Foreign Aid Allocations

This paper is designed to understand the relationship between states and nongovernmental organizations (NGOs), especially foreign aid policy and the field activities of NGOs. In this study, I argue that NGOs influence states’ foreign aid policy behaviors toward other states directly, functioning as information providers and lobbying groups. By applying theoretical arguments to the field of international development, the influence of NGOs on states’ decisions about foreign aid is analyzed with the case of the United States. A new time-series cross-sectional data set of the activities of US-based NGOs in developing countries is constructed. This study shows that as the number of US-based NGO field operations in developing countries increases, that country is significantly more likely to receive higher amounts of aid from the United States. NGOs that have longer operations in developing countries are also more effective at lobbying the United States to provide more foreign aid.

The Effect of Authorita rian Regime Type on Exchange Rate Policy

Conventional wisdom holds that autocracies are more likely than democracies to adopt interventionist and protectionist economic policies, including fixed and undervalued exchange rates. This article suggests that this view is only partially correct: nondemocracies are a heterogeneous grouping, and only some types of authoritarian regimes adopt different foreign economic policies from those of their democratic counterparts. Using the example of exchange rate policy, the authors show that foreign economic policy varies across monarchic, military, and civilian dictatorships. More specifically, they hypothesize that monarchies and military regimes are more likely than democracies and civilian dictatorships to maintain fixed exchange rate regimes because the former regimes have smaller “selectorates” than the latter. The authors also expect that monarchies and civilian dictatorships maintain more undervalued exchange rates than democracies and military regimes because the former regimes provide their leaders with greater tenure security than the latter regimes. These hypotheses are evaluated using a time-series–cross-sectional data set of a large sample of developing countries from 1973 to 2006. The statistical results accord with these predictions. These findings indicate that the ways in which democracies engage with the global economy may be less unique than many believe.

Niche Party Success and Mainstream Party Policy Shifts – How Green and Radical Right Parties Differ in Their Impact

This article investigates the impact of niche party success on the policy agendas of mainstream parties. Following from the expected electoral effects of issue politicization, the success of radical right and green parties will cause different reactions from mainstream parties. While mainstream parties emphasize anti-immigrant positions in response to radical right success, green party success will have the opposite effect for environmental issues. Since green parties constitute issue owners, their success will make established parties de-emphasize the environment. Analyzing time-series cross-section data for sixteen Western European countries from 1980 to 2011, this article empirically establishes that green and radical right parties differ in their effect on mainstream party behavior and that their impact depends on the ideological position and past electoral performance of the mainstream parties.