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This paper investigates the divergence of environmental, social, and governance (ESG) ratings based on data from six prominent ESG rating agencies: Kinder, Lydenberg, and Domini (KLD), Sustainalytics, Moody’s ESG (Vigeo-Eiris), S&P Global (RobecoSAM), Refinitiv (Asset4), and MSCI. We document the rating divergence and map the different methodologies onto a common taxonomy of categories. Using this taxonomy, we decompose the divergence into contributions of scope, measurement, and weight. Measurement contributes 56% of the divergence, scope 38%, and weight 6%. Further analyzing the reasons for measurement divergence, we detect a rater effect where a rater’s overall view of a firm influences the measurement of specific categories. The results call for greater attention to how the data underlying ESG ratings are generated.

COVID-19 highlighted the weaknesses in the supply chain. Many have argued that a more resilient or robust supply chain is needed. But what does a robust supply chain mean? And how do firms’ decisions change when taken that approach? This paper studies a very stylized model of a supply chain, where we study how the decision of a multinational corporation changes in the presence of uncertainty. The two standard theories of supply chain are just-in-time and just-in-case. Just-in-time argues in favor of pursuing efficiency, while just-in-case studies how such decision changes when the firm faces idiosyncratic risk. We find that a robust supply chain is very different specially in the presence of systemic shocks. In this case, firms need to concentrate on the worst-case. This strategy implies a supply chain where the allocation of resources and capabilities does not correspond to the standard theories studied in economics, but follow a heuristic behavioral rule called “probability matching.” It has been found in nature and in experimental research that subjects appeal to probability matching when seeking survival. We find that a robust supply chain will reproduce this behavioral outcome. In fact, a multinational optimizing under uncertainty follows a probability matching which leads to an allocation that is suboptimal from the individual producer point of view, but rules out the possibility of supply disruptions.

New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both inflation measurement and some fundamental research questions in macro and international economics. In particular, we show how online prices can be used to construct daily price indexes in multiple countries and to avoid measurement biases that distort evidence of price stickiness and international relative prices. We emphasize how Big Data technologies are providing macro and international economists with opportunities to stop treating the data as “given” and to get directly involved with data collection., Sloan School of Management

Does membership in a currency union matter for a country’s international relative prices? The answer to this question is critical for thinking about the implications of joining (or exiting) a common currency area. This paper is the first to use high-frequency good-level data to provide evidence that the answer is yes, at least for an important subset of consumption goods. It considers the case of Latvia, which recently dropped its pegged exchange rate and joined the euro zone. The paper analyzes the prices of thousands of differentiated goods sold by Zara, the world’s largest clothing retailer. Price dispersion between Latvia and euro zone countries collapsed swiftly following entry to the euro. The percentage of goods with nearly identical prices in Latvia and Germany increased from 6 to 89 percent. The median size of price differentials declined from 7 percent to zero. If a large number of firms also behave this way, these results suggest that membership in a currency union has significant implications for a country’s real exchange rate.

Recent literature has argued that conventional measures of external sustainability – the trade balance and current account – are misleading because they omit capital gains on net foreign asset positions. We adjust the definition of the current account to include the capital gains and discuss how this may affect our thinking about external adjustment and sustainability. We do so in the context of a two-country macro-finance model of Pavlova and Rigobon (2008a) that allows exploration of the interconnections between equilibrium portfolios and external accounts' dynamics. We calibrate the model and find that it generates several testable implications, some of which have already been validated empirically. First, we establish dynamic properties of the capital-gains adjusted current account and show that they are fundamentally different from those of the conventional current account. Second, we find that capital gains have a stabilizing effect on the trade balance and the current account. Finally, we demonstrate that in response to a shock, the conventional and the capital-gains adjusted current accounts may move in opposite directions., Fondation Banque de France

This paper studies how portfolios with a global investment scope are actually allocated internationally using a unique micro dataset on U.S. equity mutual funds. While mutual funds have great flexibility to invest globally, they invest in a surprisingly limited number of stocks, around 100. The number of holdings in stocks and countries from a given region declines as the investment scope of funds broadens. This restrictive investment practice has costs. A mean-variance strategy shows unexploited gains from further international diversification. Mutual funds investing globally could achieve better risk-adjusted returns by broadening their asset allocation, including stocks held by more specialized funds within the same mutual fund family (company). This investment pattern is not explained by lack of information or instruments, transaction costs, or a better ability of global funds to minimize negative outcomes. Instead, industry practices related to organizational factors seem to play an important role.

The U. S. government’s failure to provide adequate oversight and prudent regulation of the financial markets, together with excessive risk taking by some financial institutions, pushed the world financial system to the brink of systemic failure in 2008. As a consequence of this near catastrophe, both regulators and investors have become keenly interested in developing tools for monitoring systemic risk. But this is easier said than done. Securitization, private transacting, complexity, and “flexible accounting” prevent us from directly observing the many explicit linkages of financial institutions. As an alternative, the authors introduce a measure of implied systemic risk, the absorption ratio, which equals the fraction of the total variance of a set of asset returns explained or “absorbed” by a fixed number of eigenvectors. The absorption ratio captures the extent to which markets are unified or tightly coupled. When markets are tightly coupled, they are more fragile in the sense that negative shocks propagate more quickly and broadly than when markets are loosely linked.

A central assumption of open economy macro models with nominal rigidities relates to the currency in which goods are priced, whether there is so-called producer currency pricing or local currency pricing. This has important implications for exchange rate pass-through and optimal exchange rate policy. We show, using novel transaction level information on currency and prices for U.S. imports, that even conditional on a price change, there is a large difference in the pass-through of the average good priced in dollars (25%) versus non-dollars (95%). This finding is contrary to the assumption in a large class of models that the currency of pricing is exogenous and is evidence of an important selection effect that results from endogenous currency choice. We describe a model of optimal currency choice in an environment of staggered price setting and show that the empirical evidence strongly supports the model's predictions of the relation between currency choice and pass-through. We further document evidence of significant real rigidities, with the pass-through of dollar pricers increasing above 50% in the long-run. Lastly, we numerically illustrate the currency choice decision in both a Calvo and a menu-cost model with variable mark-ups and imported intermediate inputs and evaluate the ability of these models to match pass-through patterns documented in the data.

We use high frequency data and a new econometric approach to evaluate the effectiveness of controls on capital inflows. We focus on Chile's experience during the 1990s, and investigate whether controls on capital inflows reduced Chile's vulnerability to external shocks. We recognize that changes in the controls will affect the way in which different macro variables relate to each other. In particular, we consider the case where controls co-exist with an exchange rate band aimed at managing the nominal exchange rate. We develop a methodology to deal explicitly with the interaction between these two policies. The main findings may be summarized as follows: (a) a tightening of capital controls on inflows depreciates the exchange rate and (b), we find that a tightening of capital controls increases the unconditional volatility of the exchange rate, but makes it less sensitive to external shocks.

We study the bias that arises from using censored regressors in estimation of linear models. We present results on bias in ordinary least aquares (OLS) regression estimators with exogenous censoring and in instrumental variable (IV) estimators when the censored regressor is endogenous. Bound censoring such as top-coding results in expansion bias, or effects that are too large. Independent censoring results in bias that varies with the estimation method—attenuation bias in OLS estimators and expansion bias in IV estimators. Severe biases can result when there are several regressors and when a 0–1 variable is used in place of a continuous regressor.

We study the comovement among stock prices and exchange rates in a three-good, three-country, Centre-Periphery, dynamic equilibrium model in which the Centre's agents face portfolio constraints. We characterize equilibrium in closed form for a broad class of portfolio constraints, solving for stock prices, terms of trade, and portfolio holdings. We show that portfolio constraints generate wealth transfers between the Periphery countries and the Centre, which increase the comovement of the stock prices across the Periphery. We associate this excess comovement caused by portfolio constraints with the phenomenon known as contagion. The model generates predictions consistent with other important empirical results such as amplification and flight-to-quality effects. Copyright 2008, Wiley-Blackwell.

We study issues that arise for estimation of a linear model when a regressor is censored. We discuss the efficiency losses from dropping censored observations, and illustrate the losses for bound censoring. We show that the common practice of introducing a dummy variable to “correct for” censoring does not correct bias or improve estimation. We show how censored observations generally have zero semiparametric information, and we discuss implications for estimation. We derive the likelihood function for a parametric model of mixed bound-independent censoring, and apply that model to the estimation of wealth effects on consumption.

This paper measures the effects of the risks associated with the war in Iraq on various US financial variables using a heteroskedasticity-based estimation technique. The results indicate that increases in war risk caused declines in Treasury yields and equity prices, a widening of lower-grade corporate spreads, a fall in the dollar, and a rise in oil prices. This “war risk” factor accounted for a considerable portion of the variances of these financial variables over the three months leading up to the arrival of coalition forces in central Baghdad.

Using a model incorporating the endogenous relationship between exchange rates and intervention, we show how a change in central bank policy can be used as an identification assumption. Estimating this model with simulated GMM for daily data from Australia and Japan, we find that a US$100 million purchase appreciates the Australian dollar by 1.3–1.8% but the yen by just 0.2%. Almost all of the impact of an intervention occurs during the day it is conducted and we confirm that central banks typically lean against the wind.

The empirical literature on ‘contagion’ focuses mainly on two questions: (1) what are the channels through which shocks are transmitted across countries, trade, macro similarities, financial weaknesses, or investor behavior? (2) Is there a shift in the transmission of shocks during crises? Are crises spread with higher intensity? If so, why? This paper concentrates on the econometric problems that arise in dealing with the second question. The data where most of these issues are raised are plagued with problems of simultaneous equations, omitted variables, and heteroskedasticity. The standard methodologies used in the literature are inappropriate if all three are present. This paper applies a new procedure that allows one to test for parameter stability, taking into account all three predicaments. The paper tests for the stability of the transmission mechanisms among 36 stock markets during the last three major international financial crises (Mexico 1994, Asia 1997, and Russia 1998).

This paper develops a method for solving the identification problem that arises in simultaneous-equation models. It is based on the heteroskedasticity of the structural shocks. For simplicity, I consider heteroskedasticity that can be described as a two-regime process and show that the system is just identified. I discuss identification under general conditions, such as more than two regimes, when common unobservable shocks exist, and situations in which the nature of the heteroskedasticity is misspecified. Finally, I use this methodology to measure the contemporaneous relationship between the returns on Argentinean, Brazilian, and Mexican sovereign bonds-a case in which standard identification methodologies do not apply. © 2003 President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Some of the most influential theories of contagion are those based on liquidity arguments. Nevertheless, very little evidence exists on their importance. This paper shows that liquidity-based stories are responsible for one-fourth of the observed correlation in sovereign debt. Mexico was upgraded from non-investment to investment grade in March of 2000. This paper examines the impact of this event on the properties of the transmission of shocks between Mexico and several Latin American countries. The paper shows that there is a statistically significant change in the propagation of shocks around the time the upgrade was announced. Moreover, the change in the estimated coefficients can explain between one-fourth and a third of the unconditional co-movement that these assets experienced before the upgrade. This is strong evidence in favor of the theories of contagion based on market structure as the source of the propagation mechanism. From the methodological point of view, the paper extends existing identification procedures that solve the problem of estimation in linear simultaneous equations models. The methodology can be used in other Macro and Finance applications where problems of simultaneous equations represent important limitations in the estimation.

Heteroskedasticity biases tests for contagion based on correlation coefficients. When contagion is defined as a significant increase in market comovement after a shock to one country, previous work suggests contagion occurred during recent crises. This paper shows that correlation coefficients are conditional on market volatility. Under certain assumptions, it is possible to adjust for this bias. Using this adjustment, there was virtually no increase in unconditional correlation coefficients (i.e., no contagion) during the 1997 Asian crisis, 1994 Mexican devaluation, and 1987 U.S. market crash. There is a high level of market comovement in all periods, however, which we call interdependence.