Discrete choice data allow researchers to recover differences in utilities, but these differences may not suffice to identify policy-relevant counterfactuals of interest. In fact, in the case of dynamic discrete choice models, only a narrow set of counterfactuals are point-identified. In this paper, we explore how much one can learn about counterfactual outcomes of interest within this framework. We focus on the partial identification of counterfactuals, while allowing for (mild) model restrictions that can gradually shrink the identified set. We derive bounds for low-dimensional objects (such as average welfare) as arguments of optimization programs, along with a uniformly valid inference procedure. Furthermore, we develop new and tractable computational tools and algorithms suitable for dealing with high-dimensional problems like this. Finally, we illustrate in Monte Carlos, as well as an empirical exercise of firms’ export decisions, the informativeness of the identified sets, and we assess the impact of (common) model restrictions on results. 

In this paper, we argue that adjustments in non-wage compensation are empirically relevant and have important implications for understanding the effects of labor supply shocks. We examine the labor market impacts of internal migration in Brazil through a shift-share approach, which combines weather-induced migration with historical settlement patterns at each destination. Our findings indicate that increasing migration inflows lead to a reduction in formal employment while simultaneously increasing informality by a similar magnitude. Like previous studies, we observe a significant negative impact on earnings in the informal sector. Additionally, we provide evidence that the proportion of formal workers receiving non-wage benefits declines, underscoring that substantial adjustments take place in the formal sector, even in a context of high informality. We interpret our results within a framework that incorporates both formal and informal labor inputs, as well as non-wage benefits, and generates predictions closely aligned with our empirical findings.

We develop a framework to bound the welfare impacts of arbi-trarily large reforms to notches using two sufficient statistics:the change in the number of households locating below the newnotch and the change in the number of households locatingbelow the old notch. Our bounds hold in a wide class of models,highlighting a new way to use reduced-form bunching evidencefor welfare analysis without making strong assumptions on theeconomic environment. We estimate these two statistics using adifference-in-difference strategy for a reform to the anti-povertyprogram Bolsa Fam ́ılia, finding that the reform’s MVPF is between 0.90-1.12.

This paper estimates the impacts of ten recently built hydroelectric power plants in the Brazilian Amazon on deforestation. Using the inventory of all sites with undeveloped hydropower potential, we apply the synthetic control method to estimate the causal impact of each power plant on forest loss. Overall, the construction of the ten plants contributed to 13 percent of the observed forest loss within a 50-kilometer radius of the construction site. Notably, this impact is solely attributed to four plants. In at least three of these plants, construction licenses were granted despite technical recommendations against them. In contrast, the remaining plants, which received technical clearance from the environmental agency, have negligible effects. These findings highlight the effectiveness of robust environmental regulations and underscore their vulnerability to high-level political interference.

Recent work shows that in macroeconomic models with non-Ricardian consumer behavior, uniform transfers are equivalent to interest rate cuts. That is, policymakers can use stimulus payments to substitute for conventional monetary policy when, say, the zero lower bound on short-term rates binds. We argue that in the same class of models, temporarily reducing consumption taxes delivers more stimulus than transfers — at the same cost to the taxpayer. Consumption tax cuts activate both income and substitution channels and prompt a strong response from all consumers across the wealth distribution. Simulating these policies in a quantitative heterogeneous agent New Keynesian model, we find output expands twice as much.

During the medieval and early modern periods the Middle East lost its economic advantage relative to the West. Recent explanations of this historical phenomenon—called the Long Divergence—focus on these regions’ distinct political economy choices regarding religious legitimacy and limited governance. We study these features in a political economy model of the interactions between rulers, secular and clerical elites, and civil society. The model induces a joint evolution of culture and political institutions converging to one of two distinct stationary states: a religious and a secular regime. We then map qualitatively parameters and initial conditions characterizing the West and the Middle East into the implied model dynamics to show that they are consistent with the Long Divergence as well as with several key stylized political and economic facts. Most notably, this mapping suggests non-monotonic political economy dynamics in both regions, in terms of legitimacy and limited governance, which indeed characterize their history.

Small open economies are known to be impacted by shocks to larger economies. This phenomenon is known as macroeconomic vulnerability. We propose and implement a novel index of macroeconomic vulnerability to foreign shocks for a given pair of a large economy and a small open economy. It uses a structural time-varying Bayesian VAR with a block-exogeneity hypothesis. The index is based on the sum of the responses of the small open economy to shocks in the large economy over time, thus allowing us to disentangle and measure the source of the shock, the impact variables, and the duration of impact. We highlight two results out of the many that our index unveils. First, we do not find a difference between the international impact of U.S. shocks during periods of crises versus stability. Second, we find that there is a growing decouple between emerging markets (EM) and developed markets (DM) on how their domestic inflation is affected by U.S. output shocks. Our approach can also be used to elucidate previously unknown transmission channels or unmeasured theoretical mechanisms. Finally, using a sample of developed and developing countries, we find that global banks do not increase the macroeconomic vulnerability of a country.

This paper analyzes how changes in the concentration of political power affect long-run development. We study Brazil’s military dictatorship whose rise to power dramatically altered the distribution of power of local political elites. We document that municipalities that were more politically concentrated prior to the dictatorship in the 1960s are relatively richer in 2000, despite being poorer initially. Our evidence suggests that this reversal of fortune was the result of the military’s policies aimed at undermining the power of traditional elites. These policies increased political competition among traditional elites, leading to better governance, more public goods, and higher income levels

The standard measure of core or underlying inflation is the inflation rate excluding food and energy prices. This paper constructs an alternative measure, the weighted median inflation rate, for 38 advanced and emerging economies using subclass level disaggretion of the CPI over 1990-2021, and compares the properties of this measure to those of standard core. For quarterly data, we find that the weighted median is less volatile than standard core, more closely related to economic slack, and more closely related to headline inflation over the next year. The weighted median also has a drawback: in most countries, it has a lower average level than headline inflation. We therefore also consider a measure of core inflation that eliminates this bias, which is based on the percentile of sectoral inflation rates that matches the sample average of headline CPI inflation.

Inflation expectations can quickly become unanchored if the central bank undermines its commitment to the inflation target. This paper exploits a sudden change in monetary policy by the Brazilian Central Bank in 2011 and microdata from a daily survey of professional forecasters to establish support for this claim. Reanchoring came only years later, after a regime shift that included a change of government. A simple model with a well-defined concept of (un)anchored inflation expectations makes sense of and offers a structural interpretation of our empirical findings.

We provide an abstract model of the interaction between culture and political institutions. The model is designed to study the political economy of elites and civil society on the determination of long-run socioeconomic activity. We characterize conditions such that the cultural traits of elites and civil society and the institutions determining their relative political power complement (substitute) each other, giving rise to a multiplier effect that amplifies (dampens) their combined ability to spur socioeconomic activity. We show how the joint dynamics may display hysteresis and oscillations, depending on the form of the interaction between elites and civil society.

We propose a model that reconciles microeconomic evidence of frequent and large price changes with sizable monetary non-neutrality. Firms incur separate lump-sum costs to change prices and to gather and process some information about marginal costs. Additional relevant information is continuously available, and can be factored into pricing decisions at no cost. We estimate the model by Simulated Method of Moments, using price-setting statistics for the U.S. economy. The model with free idiosyncratic and costly aggregate information fits well both targeted and untargeted microeconomic moments and generates more than twice as much monetary non-neutrality as the Calvo model.

The Amazon rainforests have been undergoing unprecedented levels of human-induced

disturbances. In addition to local impacts, such changes are likely to cascade following

the eastern–western atmospheric flow generated by trade winds. We propose a model of

spatial and temporal interactions created by this flow to estimate the spread of effects

from local disturbances to downwind locations along atmospheric trajectories. The

spatial component captures cascading effects propagated by neighboring regions, while

the temporal component captures the persistence of local disturbances. Importantly, all

these network effects can be described by a single matrix, acting as a spatial multiplier

that amplifies local forest disturbances. This matrix holds practical implications for

policymakers as they can use it to easily map where the damage of an initial forest

disturbance is amplified and propagated to. We identify regions that are likely to cause

the largest impact throughout the basin and those that are the most vulnerable to shocks

caused by remote deforestation. On average, the presence of cascading effects mediated

by winds in the Amazon doubles the impact of an initial damage. However, there is

heterogeneity in this impact. While damage in some regions does not propagate, in

others, amplification can reach 250%. Since we only account for spillovers mediated

by winds, our multiplier of 2 should be seen as a lower bound

We augment a standard dynamic general equilibrium model with financial frictions, in order to quantify the macroeconomic effects of the credit deepening process observed in Latin America in the 2000s—most notably in Brazil. In the model, a stylized banking sector intermediates credit from patient households to impatient households and entrepreneurs. Motivated by the Brazilian experience, we allow the credit constraint faced by households to depend on labor income. Our model is designed to isolate the effects of credit deepening through demand-side channels, and abstracts from potential effects of credit supply on total factor productivity. In the calibrated model, credit deepening generates only modest above-trend growth in consumption, investment, and GDP. Since Brazil has experienced one of the most intense credit deepening processes in Latin America, we argue the quantitative effects that hinge on the channels captured by the model are unlikely to be sizable elsewhere in Latin America.

This paper elucidates the willingness of an autocrat to push through institutional reforms in a context where traditional authorities represented by religious clerics are averse to them and where the military control the means of repression and can potentially stage a coup. We show that although the autocrat always wants to co-opt the military, this is not necessarily true of the clerics. Exclusive co-option of the military obtains where the loyalty of the autocrat’s army is strong while the organizational strength of religious movements is rather low. Radical institutional reforms can then be implemented. Empirically, the dominant regime in contemporary Muslim countries is the regime of double co-option where the autocrat resorts to a double-edged tactic: pleasing the official clerics by slowing the pace of reforms and ensuring the loyalty of the military so as to put down clerics-led rebellions.

This paper provides a simple model of identity salience that is applied to the phenomenon of the recent rise in right-wing populism in the Western world. Trade and capital flows, skill-biased technological change, and migration have led to declining employment and wages in these economies and a parallel rise in economic and cultural populism, tapping into nativist sentiments. We argue that when long-term income stagnation for most of the population and decline for some go together with high rates of income growth at the very top, one has zero-sum economics and that naturally raises the possibility of using various kinds of social identities to claim a bigger share of a fixed sized pie. We show that in ethnically or racially polarized societies this naturally leads to the salience of social identities that enable majority ethnic groups to vote for policies that exclude minority groups so that they get a greater share of a dwindling surplus. In contrast, in more ethnically and racially homogeneous societies, this would instead lead to the demand for more pro-redistribution policies that involve greater provision of public goods.

This paper sets out a data-driven approach for targeting environmental policies optimally in order to combat deforestation. We focus on the Amazon, the world's most extensive rainforest, where Brazil's federal government issued a `Priority List' of municipalities in 2008 { a blacklist to be targeted with more intense environmental monitoring and enforcement. First, we estimate the causal impact of the Priority List on deforestation (along with other relevant treatment effects) using `changes-in-changes' (Athey and Imbens, 2006), finding that it reduced deforestation by 43 percent and cut emissions by 49 million tons of carbon. Second, we develop a novel framework for computing targeted optimal blacklists that draws on our treatment effect estimates, assigning municipalities to a counterfactual list that minimizes total deforestation subject to realistic resource constraints. We show that the ex-post optimal list would result in carbon emissions

We provide a new theory for nodewise regression when the residuals from a fitted factor model are used. We apply our results to the analysis of the consistency of Sharpe Ratio estimators when there are many assets in a portfolio. We allow for an increasing number of assets as well as time observations of the portfolio. Since the nodewise regression is not feasible due to the unknown nature of idiosyncratic errors, we provide a feasible-residual-based nodewise regression to estimate the precision matrix of errors which is consistent even when number of assets, p, exceeds the time span of the portfolio, n. In another new development, we also show that the precision matrix of returns can be estimated consistently, even with an increasing number of factors andp>n. We show that: (1) withp>n, the Sharpe Ratio estimators are consistent in global minimum-variance and mean–variance portfolios; and (2) withp>n, the maximum Sharpe Ratio estimator is consistent when the portfolio weights sum to one; and (3) withp<