Although recent articles have stressed the importance of testing for unit roots and cointegration in time-series analysis, practitioners have been left without a straightforward procedure to ...implement this advice. I propose using the autoregressive distributed lag model and bounds cointegration test as an approach to dealing with some of the most commonly encountered issues in time-series analysis. Through Monte Carlo experiments, I show that this procedure performs better than existing cointegration tests under a variety of situations. I illustrate how to implement this strategy with two step-by-step replication examples. To further aid users, I have designed software programs in order to test and dynamically model the results from this approach.
Despite a vast number of articles, the political budget cycle literature contains many conflicting theories and empirical results. I conduct the first ever meta-analysis of this literature in order ...to establish whether a link between elections and government budgets exists. Using data on 1198 estimates across 88 studies published between 2000 and 2015, I find evidence of a statistically significant—yet substantively small—increase in government expenditures and public debt around elections, and reductions in revenues and fiscal balance. Using meta-regression analysis combined with Bayesian model averaging, I find support for some of the context-conditional theories in the literature. Although the findings of political budget cycles are robust to publication bias as well as some of the methodological- and study-specific choices authors are forced to make, they also shed light on how certain decisions may affect a study’s findings. This has implications for current and future research on political budget cycles.
One potential consequence of increasing women's numeric representation is that women elected officials will behave differently than their men counterparts and improve women's substantive ...representation. This study examines whether electing women to local offices changes how local government expenditures are allocated in ways that benefit women. Using compositional expenditure data from more than 5,400 Brazilian municipalities over eight years, we find significant differences in the ways men and women mayors allocate government expenditures. Our findings indicate that women mayors spend more on traditionally feminine issues, and less on traditionally masculine issues, relative to men mayors. In regard to specific policy areas, we find that women spend more on women's issues, including education, health care, and social assistance, and less on masculine issues, including transportation and urban development, relative to men mayors. We further find that women's legislative representation significantly influences the allocation of expenditures as a larger percentage of women councilors increases spending on traditionally feminine issues, as well as education, health care, and social assistance, relative to other policy issues. These findings indicate that women local elected officials improve women's substantive representation by allocating a larger percentage of expenditures to issues that have historically and continue to concern women in Brazil.
Does the @realDonaldTrump really matter to financial markets? Research shows that new information about the likely future policy direction of government affects financial markets. In contrast, we ...argue that new information can also arise about the likely future government's resolve in following through with its policy goals, affecting financial markets as well. We test our argument using data on U.S. President Donald J. Trump's Mexico-related policy tweets and the U.S. dollar/Mexican peso exchange rate. We find that Trump's Mexico-related tweets raised Mexican peso volatility while his policy views were unknown as well as thereafter, as they signaled his resolve in carrying out his Mexico-related agenda. By helping politicians disseminate policy information to voters, and since voters hold governments accountable for their policy performance, social media allows investors to gather information about the likely policy direction and policy resolve of government, especially those of newcomers whose direction and resolve are unknown.
Abstract
Quotas have helped women achieve greater numerical representation in government around the world. Yet do they have indirect effects on representation elsewhere? We take advantage of ...plausibly exogenous variation in when and which states enacted legislation mandating 50% women’s representation in the lowest level of government in India to analyze how quotas affect women’s candidacy, vote share, and winning probability at the state level of government. We find that women are more likely to compete and win for the higher political office when women reservation is implemented at the local levels of political governance. This suggests that gender quotas have spillover effects onto other levels in politics. As women continue to be under-represented in politics, this paper highlights the role of policy instruments in shaping political careers for women and building inclusive political institutions.
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.
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.
The substance of politics involves competition that evolves over time. While our theories about competition emphasize trade-offs across multiple categories, most empirical models tend to oversimplify ...them by considering trade-offs between one category and everything else. We propose a research strategy for testing theories about trade-off relationships that shape dynamic compositional variables. This approach improves current methods used to analyze compositional dependent variables by addressing two limitations. First, although scholars have considered compositional dependent variables, they have done so in contexts that were not dynamic. Second, current approaches toward graphical presentations become unwieldy when the compositional dependent variable has more than three categories. We demonstrate the utility of our strategy to expand current theories of party support and political budgeting. In both cases, we can extend trade-offs across pairs of alternatives (e.g., prime minister versus all other parties or spending on defense versus everything else) to competition across multiple alternatives.
Mummolo and Peterson improve the use and interpretation of fixed-effects models by pointing out that unit intercepts fundamentally reduce the amount of variation of variables in fixed-effects models. ...Along a similar vein, we make two claims in the context of random effects models. First, we show that potentially large reductions in variation, in this case caused by quasi-demeaning, also occur in models using random effects. Second, in many instances, what authors claim to be a random effects model is actually a pooled model after the quasi-demeaning process, affecting how we should interpret the model. A literature review of random effects models in top journals suggests that both points are currently not well understood. To better help users interested in improving their interpretation of random effects models, we provide Stata and R programs to easily obtain post-estimation quasi-demeaned variables.
Objective
The study aims to demonstrate the utility of modeling compositional volatility in substantive domains beyond budgeting.
Methods
We show how to model compositional volatility on its own or ...as a part of a system of equations in which the component parts of the compositional outcome variable are also modeled.
Results
Using data on the volatility of support for German political parties, we demonstrate the usefulness of stand‐alone models of compositional volatility. Using data on the volatility of income shares in the United States, we demonstrate the usefulness of modeling volatility together with compositional components.
Conclusion
There is considerable potential for modeling compositional volatility.
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