Knowledge that Transforms

We show that the entry of formal financial institutions can have far-reaching and long-lasting impacts on informal lending and social networks more generally. We first study the introduction of microfinance in 75 villages in Karnataka, India, 43 of which were exposed to microfinance. Using difference-in-differences, we show that networks shrank more in exposed villages. Moreover, links between households that were both unlikely to borrow from microfinance were at least as likely to disappear as links involving likely borrowers. We replicate these surprising findings in the context of a randomised controlled trial (RCT) in Hyderabad, where a microfinance institution randomly selected 52 of 104 neighbourhoods to enter first. Four years after all neighbourhoods were treated, households in early-entry neighbourhoods had credit access longer and had larger loans. We again find fewer social relationships between households in these neighbourhoods, even among those ex-ante unlikely to borrow. Because the results suggest global spillovers, atypical in usual models of network formation, we develop a new dynamic model of network formation that emphasizes chance meetings, where efforts to socialize generate a global network-level externality. Finally, we analyse informal borrowing and the sensitivity of consumption to income fluctuations. Households unlikely to take up microcredit suffer the greatest loss of informal borrowing and risk sharing, underscoring the global nature of the externality.

Diagnostic expectations constitute a realistic behavioural model of inference. This paper shows that this approach to expectation formation can be productively integrated into the New Keynesian framework. Diagnostic expectations generate endogenous extrapolation in general equilibrium. We show that diagnostic expectations generate extra amplification in the presence of nominal frictions; a fall in aggregate supply generates a Keynesian recession; fiscal policy is more effective at stimulating the economy. We perform Bayesian estimation of a rich medium-scale model that incorporates consensus forecast data. Our estimate of the diagnosticity parameter is in line with previous studies. Moreover, we find empirical evidence in favour of the diagnostic model. Diagnostic expectations offer new propagation mechanisms to explain fluctuations.

Based on an asset demand system, we develop a framework to quantify the impact of market trends and changes in regulation on asset prices, price informativeness, and the wealth distribution. Our leading applications are the transition from active to passive investment management and climate-induced shifts in asset demand. The transition from active to passive investment management had a large impact on equity prices but a small impact on price informativeness because capital did not flow from more to less informed investors on average. This finding is based on a new measure of investor-level informativeness that identifies which investors are more informed about future profitability. Climate-induced shifts in asset demand have a potentially large impact on equity prices and the wealth distribution, implying capital gains for passive investment advisors, pension funds, insurance companies, and private banking and capital losses for active investment advisors and hedge funds.

The U.K. economy experienced significant macroeconomic adjustments following the 2016 referendum on its withdrawal from the European Union. To understand these adjustments, this paper presents empirical facts using novel U.K. macroeconomic data and estimates a small open economy model with tradable and non-tradable sectors. We demonstrate that the referendum outcome can be interpreted as news about a future decline in productivity growth in the tradable sector. An immediate fall in the relative price of non-tradable goods induces a temporary “sweet spot” for tradable producers. Economic activity in the tradable sector expands in the short run, while the non-tradable sector contracts. Aggregate output, consumption, and investment growth decelerate.

What determines the distribution of establishments in terms of size and life-cycle growth? How are those determinants related to aggregate productivity? We provide novel answers by developing a framework that uses price and quantity information on establishments’ outputs and inputs to jointly estimate the demand and production parameters, and subsequently, establishments’ quality-adjusted productivity, deriving both micro-level and aggregate implications. We find that the dominant source of variation in establishment size is variation in quality/product appeal but that variation in technical efficiency plays an important supporting role. Multiple factors dampen dispersion in establishment size including dispersion in input (quality-adjusted) prices, markups, and residual wedges. Relatively moderate dampening factors induce large aggregate allocative efficiency losses relative to their absence. We show that joint estimation of the parameters of the demand and production function crucially affects inferences on the determinants of the size distribution of firms and their implications for aggregate productivity.

We explore the impact of rising incomes at the top of the distribution on spatial sorting patterns within large U.S. cities. We develop and quantify a spatial model of a city with heterogeneous agents and non-homothetic preferences for neighbourhoods with endogenous amenity quality. As the rich get richer, demand increases for the high-quality amenities available in downtown neighbourhoods. Rising demand drives up house prices and spurs the development of higher quality neighbourhoods downtown. This gentrification of downtowns makes poor incumbents worse off, as they are either displaced to the suburbs or pay higher rents for amenities that they do not value as much. We quantify the corresponding impact on well-being inequality. Through the lens of the quantified model, the change in the income distribution between 1990 and 2014 led to neighbourhood change and spatial resorting within urban areas that increased the welfare of richer households relative to that of poorer households, above and beyond rising nominal income inequality.

We study how cross-country macroeconomic spillovers caused by sovereign default affect equilibrium bailouts. Because of portfolio diversification, the default of one country causes a macroeconomic contraction in other countries, which motivates a bailout. But why do creditor countries choose to bailout debtor countries instead of their own private sector? We show that this is because an external bailout could be cheaper than a domestic bailout. We also show that although anticipated bailouts lead to higher borrowing, they can be Pareto improving not only ex post (after a country has defaulted) but also ex ante (before the country chooses its debt).

We develop a model of the global financial cycle with one key ingredient: the international demand for safe dollar assets. The model matches patterns of dollar borrowing and currency mismatch, the U.S. external balance sheet, exorbitant privilege, spillovers of the U.S. monetary policy to the rest of the world, and the dollar as a global risk factor. In doing so, we lay out a novel transmission mechanism through which the U.S. monetary policy affects the currency market and the global economy. The global financial cycle is a dollar cycle.

This paper is concerned with possible model misspecification in moment inequality models. Two issues are addressed. First, standard tests and confidence sets for the true parameter in the moment inequality literature are not robust to model misspecification in the sense that they exhibit spurious precision when the identified set is empty. This paper introduces tests and confidence sets that provide correct asymptotic inference for a pseudo-true parameter in such scenarios, and hence, do not suffer from spurious precision. Second, specification tests have relatively low power against a range of misspecified models. Thus, failure to reject the null of correct specification does not necessarily provide evidence of correct specification. That is, model specification tests are subject to the problem that absence of evidence is not evidence of absence. This paper develops new diagnostics for model misspecification in moment inequality models that do not suffer from this problem.

Many e-commerce platforms use buyers’ personal data to intermediate their transactions with sellers. How much value do such intermediaries derive from the data record of each single individual? We characterize this value and find that one of its key components is a novel externality between records, which arises when the intermediary pools some records to withhold the information they contain. Our analysis has several implications about compensating individuals for the use of their data, guiding companies’ investments in data acquisition, and more broadly studying the demand side of data markets. Our methods combine modern information design with classic duality theory and apply to a large class of principal-agent problems.