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Meta-analyses are used to synthesize a body of literature to produce a single summary estimate as well as to explain differences among studies. The field of political science has slowly gained an appreciation for their use in recent years; however, using meta-analyses in dissertations remains rare. This is puzzling, given the tool’s ability to map a topic, to highlight potential gaps for future research to address, and its long-lasting utility for researchers in future projects. We argue that for these and several other reasons, graduate students should consider including a meta-analysis in their dissertation. This article discusses these advantages in detail and offers advice on how to conduct a meta-analysis based on several interviews and applied examples. We also address potential challenges when using this research design in a dissertation.
In Chapter 4, we continue our explanation of tradeoffs between expenditure categories by focusing on how domestic and international contextual factors can constrain or facilitate government budgetary behavior. For the domestic contexts, we consider election timing, unemployment, and economic growth. In the international realm, we focus on globalization and conflict involvement. For each of these contextual factors, we develop a set of expectations about the spending tradeoffs between policy areas if left and right governments remain ideologically consistent to their preferences versus if context overwhelms those ideological concerns. Our results and conclusions are mixed across the domestic contexts. We find almost no tradeoffs and none that are consistent with either type of expectations for election timing. For an increasing unemployment, we find a mixture of ideological and strategic tradeoff decisions, while, for positive economic growth, we find substantial evidence that governments take advantage of the circumstances to go beyond their ideological priorities. Results for international contexts are also mixed with government spending allocations lacking ideological differences in the face of increased globalization. But, for increased conflict, right and left governments reallocate expenditures in similar ways – highlighting how contexts can overwhelm governments.
Whether domestic and international contexts affect governments’ abilities to alter total expenditures, revenues, deficits, and budgetary volatility is our focus in Chapter 6. We develop expectations about the influence of government ideology and majority status together with contextual factors and other budgetary components on each of our four budgetary components. For the domestic contexts, we consider election timing, unemployment, and economic growth. In the international realm, we focus on globalization and conflict involvement. Building on the results from the panel vector autoregressive (pVAR) model from Chapter 5, we specify separate reduced-form models for each of our budget component variables to test our theoretical expectations. Across the results we present in this chapter, we find very few statistically significant effects, especially in terms of long-run effects, on the four budgetary components. The strongest results are for the influence of contextual factors on budgetary volatility, specifically when increasing unemployment and economic openness. When unemployment or economic openness increases, we find that budgetary volatility increases under majority left governments in both the short- and long-runs. This evidence indicates that right and left governments differ in how much they respond to both domestic and international contexts.
Government budgets can be complex and contentious. Chapter 1 explains the importance of understanding government budgetary behavior and argues for taking a more realistic view of the process. If governments change part of the budget, then they may need to jostle other budgetary pieces as well. We introduce the broad brushstrokes of our theoretical argument that explains when governments have the desire and power to alter budgets, given both their ideological preferences and contextual factors. We acknowledge that spending increases or decreases in some policy areas may require shifts in budgets for other areas, so we use a compositional methodological approach to investigate those changes. In addition, we foreshadow how our theoretical argument also helps to explain the linkages between expenditures, revenues, deficits, and budgetary volatility. To test theories about these linkages we use panel vector autoregressive (pVAR) models. In order to make our findings from the complex models that we use to test our theoretical propositions accessible, we will use a series of graphical interpretation strategies and present technical details of our models and graphs in appendices. Overall, Chapter 1 sets the stage for a book that unravels the brainteaser of government budgetary behavior across countries and years.
In Chapter 3, we focus on explaining the tradeoffs between expenditure categories in government budgets. Rather than explain total expenditures or expenditures in specific policy areas, we argue that the competition for expenditures is in the spending allocations. Governments of varying ideological stances prefer increasing or decreasing spending for different policy areas, but we argue that their ability to do this is hindered by their government status. Governments with a majority of the seats in the lower house of parliament are better able to push through their preferred changes to spending budgets. Using a compositional methodological approach on data for 33 developed democracies across 35 years (1975–2010), we find that government ideology does influence budgetary allocations for majority governments, with left and right governments altering budgets in different, but expected, ways. For minority governments, our results suggest they too are strategic in making relative budgetary changes, but it is less about ideology and more about appeasing the necessary political parties in order to stay in power. This focus on budgetary compositions highlights the political competition for resources between policy areas that previous work has overlooked.
In Chapter 7, we conclude by placing both our theoretical and methodological contributions within the wider world of government decision-making. Our theory begins with the core assumption that government ideology drives the budgetary priorities of governments. With a blank slate, these ideological preferences would steer governments in shaping budgets. While this is a useful place to start theoretical debate about political budgeting, an important part of our argument is about how contextual factors influence whether governments can achieve their ideological priorities. Throughout the book, we find many instances in which context overwhelms ideology to drive government budgets. In developing our theoretical ideas about the interplay between ideology and contexts, we emphasize the importance of recognizing the interlinked nature of the different parts of political budgets. We take advantage of recent advances in dynamic compositional models and panel vector autoregressive (pVAR) models when testing our ideas. To make the results from these complex models accessible, we rely heavily on graphical presentations of our findings. Together, our theory of budgets and the methods we use to test it are all intended to bring studies closer to the messy but fascinating real world of political budgeting.
We turn to the larger pieces of the budget in Chapter 5, where we focus on two objectives. First, we ask how the components of the budgets fit together by conducting causality tests for the full range of possible relationships between expenditures, revenues, deficits, and budgetary volatility using a panel vector autoregressive (pVAR) model. We find that changes to expenditures and revenues drive changes to deficits, and we also find that changes to deficits lead to revenue changes. Second, using findings from these causality tests from the pVAR model, we then test our expectations about ideology and context on total spending, revenues, budget deficits, and budgetary volatility. Once we include these causal relationships in our models, we find that government ideology and majority status do not appear to alter either total expenditures or revenues, but a shift from a left to a right majority government is associated with a long-run decrease in deficits. For budgetary volatility, a move from a left to a right majority government corresponds with a positive significant increase in volatility. These findings fit our expectations that it is political competition that shifts budgets, with government ideology many times proctoring for those differences.
In Chapter 2, we begin with a discussion of the vast literature on political budgeting. We identify three main types of approaches in the extant literature – studies focusing on single budgetary categories, studies of budgetary changes, and studies of aggregate budgetary components. While each of these approaches has provided helpful insights into the relationships between politics and budgeting, they have ignored or greatly simplified the complex tradeoffs and interworkings of budgetary components. Our theoretical argument of political budgeting engages with both the compositional tradeoffs that occur across expenditure categories and the simultaneous interplay between expenditures, revenues, budgetary volatility, and deficit components of budgets. We argue that government ideology and the priorities of core supporters of governments drive their general budgetary priorities; however, domestic and international contexts can make it easier or harder for governments to implement these priorities. Focusing on the contexts of government power, electoral timing, economic conditions, globalization, and conflict affect governments’ budgetary abilities, we put forth a theoretical argument that governments may be unable to fulfil their ideological preferences when external contexts constrain their behavior.
While governments prefer to alter budgets to fit their ideological stances, the domestic and international contexts can facilitate or constrain behavior. The Politics of Budgets demonstrates when governments do and do not make preferred budgetary changes. It argues for an interconnected view of budgets and explores both the reallocation of expenditures across policy areas and the interplay among budgetary components. While previous scholars have investigated how politics and economics shape a single budgetary category, or collective categories, this methodologically rich study analyzes data for thirty-three countries across thirty-five years to provide a more comprehensive theoretical approach: a 'holistic' framework about the competition and contexts around the budgetary process and an of examination of how and when these factors affect the budgetary decision-making processes.
Decades of research has debated whether women first need to reach a “critical mass” in the legislature before they can effectively influence legislative outcomes. This study contributes to the debate using supervised tree-based machine learning to study the relationship between increasing variation in women's legislative representation and the allocation of government expenditures in three policy areas: education, healthcare, and defense. We find that women's representation predicts spending in all three areas. We also find evidence of critical mass effects as the relationships between women's representation and government spending are nonlinear. However, beyond critical mass, our research points to a potential critical mass interval or critical limit point in women's representation. We offer guidance on how these results can inform future research using standard parametric models.
A flurry of current interest in time series has focused on clarifying equation balance, fractional integration, and cointegration testing. Despite this, a number of recent suggestions may continue to lead scholars toward incorrect inferences. In this comment, I investigate the likelihood of drawing both correct and incorrect inferences under a variety of stationary and non-stationary data-generating processes. I extend previous work in this area by focusing on both short- and long-run effects using several popular model specifications. Given these findings, I conclude by offering a variety of recommendations to practitioners about how they can best specify their model.