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Women earn less than men who work in the same job with the same level of experience. We know much about this gender wage gap but relatively little about its political or partisan sources. In this article, we examine the effects of party control of state government on gender inequality in income, wages, unemployment, and poverty. Employing both a regression discontinuity design and a dynamic difference-in-difference analysis, we find that electing a Democratic majority to the state house leads to substantial improvement in women’s incomes, wages, and unemployment relative to men – especially in recent years. We also show that greater female representation in office and more liberal policy-making on policies related to women’s rights could be driving that process. We find, however, fewer clear effects on poverty and less robust results for partisan control of the governor’s office or the state senate. Parties and politics matter, but not always.

Critics of the recent proliferation of strict photo identification laws claim these laws impose a disproportionate burden on racial minorities. Yet, empirical studies of the impact of these laws on...

As more urban residents find their housing through online search tools, recent research has theorized the potential for online information to transform and equalize the housing search process. Yet, very little is known about what rental housing information is available online. Using a corpus of millions of geocoded Craigslist advertisements for rental housing across the 50 largest metropolitan statistical areas in the United States merged with census tract–level data from the American Community Survey, we identify and describe the types of information commonly included in listings across different types of neighborhoods. We find that in the online housing market, renters are exposed to fundamentally different types of information depending on the ethnoracial and socioeconomic makeup of the neighborhoods where they are searching.

Past research has demonstrated the racially and spatially uneven impacts of economic shocks and environmental disasters on various markets. In this article, we examine if and how the first few months of the COVID-19 pandemic affected the market for rental housing in the 49 largest metropolitan areas in the United States. Using a unique data set of new rental listings gathered from Craigslist and localized measures of the pandemic’s severity we find that, from mid-March to early June, local spread of COVID-19 is followed by reduced median and mean rent. However, this trend is driven by dropping rents for listings in Black, Latino, and diverse neighborhoods. Listings in majority White neighborhoods experience rent increases during this time. Our analyses make multiple contributions. First, we add to the burgeoning literature examining the rental market as a key site of perpetuating sociospatial inequality. Second, we demonstrate the utility of data gathered online for analyzing housing. And third, by reflecting on research that shows how past crises have increased sociospatial inequality and up-to-date work showing the racially and spatially unequal effects of the COVID-19 pandemic, we discuss some possible mechanisms by which the pandemic may be affecting the market for rental housing as well as implications for long-term trends.

Housing scholars stress the importance of the information environment in shaping housing search behavior and outcomes. Rental listings have increasingly moved online over the past two decades and, in turn, online platforms like Craigslist are now central to the search process. Do these technology platforms serve as information equalizers or do they reflect traditional information inequalities that correlate with neighborhood sociodemographics? We synthesize and extend analyses of millions of US Craigslist rental listings and find they supply significantly different volumes, quality, and types of information in different communities. Technology platforms have the potential to broaden, diversify, and equalize housing search information, but they rely on landlord behavior and, in turn, likely will not reach this potential without a significant redesign or policy intervention. Smart cities advocates hoping to build better cities through technology must critically interrogate technology platforms and big data for systematic biases.

Voter ID laws determine who can and who cannot vote. Given the recent propagation of these laws by Republican legislatures, efforts by the Trump administration and other state legislatures to expan...

Mounting import competition from China has increased unemployment in manufacturing and suppressed wages in local labor markets around the United States. This article investigates the political effe...

In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social solidarity? Comparative cross-national research, relying mostly on secondary data, has findings in different directions. There is a threat of selective model reporting and lack of replicability. The heterogeneity of countries obscures attempts to clearly define data-generating models. P-hacking and HARKing lurk among standard research practices in this area.This project employs crowdsourcing to address these issues. It draws on replication, deliberation, meta-analysis and harnessing the power of many minds at once. The Crowdsourced Replication Initiative carries two main goals, (a) to better investigate the linkage between immigration and social policy preferences across countries, and (b) to develop crowdsourcing as a social science method. The Executive Report provides short reviews of the area of social policy preferences and immigration, and the methods and impetus behind crowdsourcing plus a description of the entire project. Three main areas of findings will appear in three papers, that are registered as PAPs or in process.

Mounting import competition from China has increased unemployment in manufacturing and suppressed wages in local labor markets around the United States . This article investigates the political effects of this China trade shock, using a unique dataset of the district-level economic impact of Chinese imports to the United States. The liberalization of trade following China's accession to the World Trade Organization increased political polarization among American voters and encouraged legislators in economically hard-hit districts to take positions hostile to China. The result is that Congress is even more hostile towards China today than in the aftermath of the Tiananmen Massacre. After 2003, members of Congress representing districts more adversely impacted by import competition were more likely to vote against China, controlling for ideology and partisanship. By contrast, import competition was not a significant predictor of earlier congressional opposition to granting most-favored nation status to China (suggesting that voting on these crucial pieces of legislation was driven by non-economic concerns such as human rights). Far from being the political win-win its proponents envisioned, trade has eclipsed human rights and Taiwan as the main driver of hostility to China in Congress.

The district-level political implications of trade competition are mitigated by the strategic behavior of incumbent legislators and the constraints placed upon them by party affiliation. In this paper, we examine the partisan difference in congressional communication strategies on China and trade related issues. We find that, even though Chinese import competition impacted both Republican- and Democrat-held districts, Republican politicians engage in more protectionist and anti-China rhetoric and policy proposals. Using press release data from members of Congress, we show that, among districts more exposed to Chinese imports, Republicans are more likely to blame China as the problem. But there is no difference between Republican and Democratic messaging on trade issues in general. We attribute this partisan shift in political communication strategy to the fact that Republican legislators are more constrained by their party platform from advocating for trade protectionism and social welfare relative to Democrats. Blaming the negative externalities of import competition on China rather than on trade policy has allowed Republican incumbents to continue to support their party’s free trade platform without alienating their constituents. This explains why candidate Trump’s protectionist message linking China and trade resonated with the Republican base much more so than proposals that were better grounded in economic realities.