I am a Lecturer (Assistant Professor) at the Hebrew University of Jerusalem Economics department.
My research interests include international finance and macroeconomics.
Research
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Sovereign Default Risk and Foreign Currency Returns
Abstract
Many currencies exhibit non-zero average returns with respect to the US dollar, in an apparent violation of textbook uncovered and covered interest parities. I first show that in the cross-section of countries foreign currency returns are positively related to sovereign default risk, and then reconcile this finding with the standard theory via the "peso problem." Market players collect a premium for bearing the risk of sharp devaluation in case of default. Since defaults are rare in the data, default premium manifests itself in higher currency returns. To formalize the link between default risk and currency returns, I discipline quantitatively a model with default based on Arellano (2008) for a set of developing countries. I then use the implications of this model to construct an econometric model for the cross-section of currency returns that I estimate using the extended Fama and MacBeth (1973) method. I find strong evidence supporting the "peso problem" explanation: credit default swap spreads, serving as a proxy for default risk, explain around 25% of the cross-country variation of average currency returns.
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Cond. Accepted at JBES Non-linear Dynamic Factor Models for Financial and Macroeconomic Applications
Abstract
Through the lens of a nonlinear dynamic factor model, we study the role of exogenous shocks and internal propagation forces in driving the fluctuations of macroeconomic and financial data. The proposed model 1) allows for nonlinear dynamics in the state and measurement equations; 2) can generate asymmetric, state-dependent, and size-dependent responses of observables to shocks; and 3) can produce time-varying volatility and asymmetric tail risks in predictive distributions. We find evidence in favor of nonlinear dynamics in two important US applications. The first uses interest rate data to extract a factor allowing for an effective lower bound and nonlinear dynamics. Our estimated factor coheres well with the historical narrative of monetary policy, and we find that allowing for an effective lower bound constraint is crucial. The second recovers a credit cycle. The nonlinear component of the factor boosts credit growth in boom times while hindering its recovery post-crisis. Shocks in a credit-crunch period are more amplified and persist for longer compared with shocks during a credit boom.
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Healthcare and the Macroeconomy
Abstract
An important question in economics is why health varies over the business cycle. Is it the result of wealth or substitution effects following a standard business cycle? Or is it because of shocks in the health segment of the economy? This paper answers that question from an empirical perspective using micro data, and a structural heterogeneous-agent model that features endogenous health risks, health expenditures, and time spent on health care.
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Why Not Borrow, Invest, and Escape Poverty?
Abstract
Take-up of microcredit by the poor for investment in businesses or human capital turned out to be very low. We show that this could be explained by risk aversion, without relying on fixed costs or other forms of non-convexity in the technology, if the investment is aimed at increasing the probability of success. Under this framework, rational risk-averse agents choose corner solutions, unlike in the case of a risky investment with an exogenous probability of success. Our online experiment confirms our theoretical predictions about how agents' choices differ when facing the two types of investments.
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All Eggs in One Basket: When Diversification Increases Portfolio Risk?
Abstract
We show that when investment increases a project's probability of success, rather than its payoff conditional on success, diversifying a fixed budget across uncorrelated projects increases overall portfolio risk. We apply this finding to venture capital, hypothesizing that risk-averse managers limit diversification to mitigate this risk. We propose a testable prediction that distinguishes our hypothesis from the conventional one without requiring direct measurement of portfolio risk. Existing empirical evidence, by and large, is consistent with our hypothesis.
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Creator Communication and Trading in NFT Markets: Evidence from a Marketplace Policy Change
Abstract
NFT project creators both inform investors and collect proportional fees on every secondary-market trade. Between 2022 and 2023, platform competition progressively eliminated mandatory creator fees. Using weekly panel data for NFT collections on Ethereum and Solana, we show that creator tweets predict trading volume, primarily through transaction counts rather than prices, and that this link attenuated when fee enforcement weakened, with larger declines for higher-fee collections. We develop a noisy rational-expectations model with heterogeneous interpretation of public signals to compare two creator-compensation schemes: per-trade royalties and revenue-equivalent upfront membership fees. Idiosyncratic interpretation noise causes more precise communication to widen belief dispersion rather than compress it, while proportional fees create inaction thresholds that amplify the effect of disagreement on volume. Under royalties, creators back-load disclosure to stimulate trades; under membership fees, they front-load it to resolve uncertainty. The welfare comparison shows that the membership scheme dominates: it eliminates per-trade distortions, and under early-resolution-of-uncertainty preferences the shift in disclosure timing provides an additional welfare gain.
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Some Apples Fall Far: Skill Premium, Housing and the Rising Price-to-Rent Ratio