Chris Roth is a postdoctoral fellow at the Institute on Behavior and Inequality. Before, he studied economics at the University of Oxford and the University of Warwick. His fields of specialization are economics & psychology, applied microeconometrics, and political economy. He is especially interested in the role of subjective beliefs in shaping economic and political behavior. Chris' work has examined a variety of topics, such as attitudes towards immigration, beliefs about racial discrimination, experimenter demand effects, the formation of macroeconomic expectations, and the determinants of political engagement. Methodologically, his work relies on online experiments, natural field experiments and laboratory experiments.

working papers

We propose a method to measure people's subjective models of the macroeconomy. Using a representative sample of the US population and a sample of experts we study how expectations about the unemployment rate and the inflation rate change in response to four di fferent hypothetical exogenous shocks: a monetary policy shock, a government spending shock, a tax shock, and an oil price shock. While expert predictions are mostly quantitatively aligned with standard dynamic stochastic general equilibrium models and vector autoregression evidence, there is strong heterogeneity in the predictions in the representative panel. While households predict changes in unemployment that are qualitatively in line with the experts for all four shocks, their predictions of changes in inflation are at odds with those of experts both for the tax shock and the interest rate shock. People's beliefs about the micro mechanisms through which the di fferent macroeconomic shocks are propagated in the economy strongly a ffect how aligned their predictions are with those of the experts. More educated and older respondents form their expectations more in line with experts, consistent with roles for cognitive limitations and learning over the life-cycle. Our fi ndings inform the validity of central assumptions about the expectation formation process and have important implications for the optimal design of scal and monetary policy.

We examine how people’s perceptions of media bias affect their demand for news. Drawing on a large representative sample of the US population, we measure and experimentally manipulate people’s beliefs about the extent to which newspapers suppress information. Inconsistent with the “more-information-is-better principle,” we find that people who learn that a newspaper is less likely to suppress information have a lower demand for news from this newspaper. Our results demonstrate that people have a demand for biased news, consistent with a desire to confirm pre-existing beliefs.

How do the decisions of citizens to engage in political activism depend on their beliefs about the engagement of others? We examine this question through a natural field experiment with a major European party during a recent high-stake election. In a seemingly unrelated party survey, we randomly assigned canvassers to true information about the canvassing intentions of their peers. Using survey evidence and unobtrusive, behavioral data from the party's canvassing app, we find that treated canvassers reduce their own canvassing signifcantly when learning that their peers engage in more canvassing than previously thought. Treatment effects are particularly large i) along the intensive margin; ii) in the final days of the campaign; iii) and for people less driven by social image concerns. The evidence implies that effort choices of
political activists exhibit strategic substitutability, not complementarity.

We examine how income shocks affect the suicide rate in Indonesia. We use both a randomized conditional cash transfer experiment, and a difference-in-differences approach exploiting the cash transfer's nation-wide roll-out. We find that the cash transfer reduced yearly suicide rates by 0.36 per 100,000 people, corresponding to an 18 percent decrease. Agricultural productivity shocks also causally affect suicide rates. Finally, we establish that cash transfers most strongly reduce suicides in the presence of negative agricultural productivity shocks, suggesting an important role for policy interventions in mitigating the consequences of adverse economic shocks.

We examine whether beliefs about the labor market impact of immigration are an important driver of support for immigration. Using a large, representative sample of the US population, we first elicit our respondents' beliefs about how immigration affects local labor markets. To introduce exogenous variation in beliefs, we provide respondents in the treatment group with research evidence showing no adverse labor market impacts of immigration. Treated respondents update their beliefs about the labor market impact of immigration and become more supportive of immigration, as measured by self-reported policy views and signatures of real online petitions. We also employ an obfuscated follow-up study which hides the connection between the follow-up and the main study from respondents. The treatment effects persist in this setting where experimenter demand is mitigated. Our results demonstrate that beliefs about the labor market impact of immigration are an important causal determinant of people's support for immigration.

Using a representative online panel from the US, we examine how individuals' macroeconomic expectations causally affect their personal economic prospects and their behavior. To exogenously vary respondents' expectations, we provide them with different professional forecasts about the likelihood of a recession. Respondents update their macroeconomic outlook in response to the forecasts, extrapolate to expectations about their personal economic circumstances and adjust their consumption plans and stock purchases. Extrapolation to expectations about personal unemployment is driven by individuals with higher exposure to macroeconomic risk, consistent with macroeconomic models of imperfect information in which people are inattentive, but understand how the economy works.

We provide representative evidence on people’s beliefs about racial discrimination against blacks and explore whether these beliefs causally affect people’s support for pro-black policies. In two online experiments, we elicit incentivized beliefs about the extent of racial labor market discrimination against blacks. We document large heterogeneity in beliefs and find particularly pronounced differences between Democrats and Republicans. To introduce exogenous variation in beliefs, we provide a random subset of our respondents with research evidence from an audit study that tested for discrimination against blacks in the labor market. We find that treated subjects strongly update their beliefs about the extent of racial discrimination against blacks in response to the information, which affects donations to a pro-black civil rights organization. However, we find muted treatment effects on support for pro-black policies, such as affirmative action and assistance programs for blacks; if anything, we find that the treatment backfires for Republicans. Overall, our results suggest that people’s beliefs about racial discrimination affect their support for pro-black civil rights organizations, but that their views on policies to combat racial discrimination are not responsive to changes in beliefs.

We examine how beliefs about the debt-to-GDP ratio affect people's attitudes towards government spending and taxation. Using a representative sample of the US population, we provide half of our respondents with information about the debt-to-GDP ratio in the US. We find that most people underestimate the debt-to-GDP ratio and reduce their support for government spending once they learn about the actual amount of debt, but do not alter their attitudes towards taxation. The treatment effects seem to operate through changes in expectations about fiscal sustainability and persist in a four-week follow-up.

We examine whether individuals' experienced levels of income inequality affect their preferences for redistribution. We use several large nationally representative datasets to show that people who have experienced higher inequality during their lives are less in favor of redistribution, after controlling for income, demographics, unemployment experiences and current macroeconomic conditions. They are also less likely to support left-wing parties and to consider the prevailing distribution of incomes to be unfair. We provide evidence that these findings do not operate through extrapolation from own circumstances, perceived relative income or trust in the political system, but seem to operate through our respondents' fairness views. Our evidence suggests that being accustomed to an unequal distribution of incomes can make people more accepting of inequality and reduce their demand for redistribution.

We study whether providing information about immigrants affects people’s attitude towards them. First, we use a large representative cross-country experiment to show that, when people are told the share of immigrants in their country, they become less likely to state that there are too many of them. Then, we conduct two online experiments in the U.S., where we provide half of the participants with five statistics about immigration, before evaluating their attitude towards immigrants with self-reported and behavioral measures. This more comprehensive intervention improves people’s attitude towards existing immigrants, although it does not change people’s policy preferences regarding immigration. Republicans become more willing to increase legal immigration after receiving the information treatment. Finally, we also measure the same self-reported policy preferences, attitudes, and beliefs in a four-week follow-up, and we show that the treatment effects persist.


We propose a technique for assessing robustness to demand effects of findings from experiments and surveys. The core idea is that by deliberately inducing demand in a structured way we can bound its influence. We present a model in which participants respond to their beliefs about the researcher’s objectives. Bounds are obtained by manipulating those beliefs with “demand treatments.” We apply the method to eleven classic tasks, and estimate bounds averaging 0.13 standard deviations, suggesting that typical demand effects are probably modest. We also show how to compute demand-robust treatment effects and how to structurally estimate the model.


research fields

Psychology and Economics

Political Economy

Beliefs and Expectations