Federal Reserve Bank of New York

ABSTRACT This paper uses a disaggregated approach to study the volatility of common stocks at the market, industry, and firm levels. Over the period from 1962 to 1997 there has been a noticeable increase in firm‐level volatility relative to market volatility. Accordingly, correlations among individual stocks and the explanatory power of the market model for a typical stock have declined, whereas the number of stocks needed to achieve a given level of diversification has increased. All the volatility measures move together countercyclically and help to predict GDP growth. Market volatility tends to lead the other volatility series. Factors that may be responsible for these findings are suggested.

Since the seminal work of Krugman, product variety has played a central role in models of trade and growth. In spite ofthe general use oflove-of-variety models, there has been no systematic study of how the import of new varieties has contributed to national welfare gains in the United States. In this paper we show that the unmeasured growth in product variety from U. S. imports has been an important source of gains from trade over the last three decades (1972–2001). Using extremely disaggregated data, we show that the number of imported product varieties has increased by a factor of three. We also estimate the elasticities of substitution for each available category at the same level of aggregation, and describe their behavior across time and SITC industries. Using these estimates, we develop an exact aggregate price index and find that the upward bias in the conventional import price index over this time period was 28 percent or 1.2 percentage points per year. We estimate the value to U. S. consumers of the expanded import varieties between 1972 and 2001 to be 2.6 percent of GDP.

This paper studies the role of fluctuations in the aggregate consumption–wealth ratio for predicting stock returns. Using U.S. quarterly stock market data, we find that these fluctuations in the consumption–wealth ratio are strong predictors of both real stock returns and excess returns over a Treasury bill rate. We also find that this variable is a better forecaster of future returns at short and intermediate horizons than is the dividend yield, the dividend payout ratio, and several other popular forecasting variables. Why should the consumption–wealth ratio forecast asset returns? We show that a wide class of optimal models of consumer behavior imply that the log consumption–aggregate wealth (human capital plus asset holdings) ratio summarizes expected returns on aggregate wealth, or the market portfolio. Although this ratio is not observable, we provide assumptions under which its important predictive components for future asset returns may be expressed in terms of observable variables, namely in terms of consumption, asset holdings and labor income. The framework implies that these variables are cointegrated, and that deviations from this shared trend summarize agents' expectations of future returns on the market portfolio.

We propose a measure of systemic risk, Δ CoVaR, defined as the change in the value at risk of the financial system conditional on an institution being under distress relative to its median state. Our estimates show that characteristics such as leverage, size, maturity mismatch, and asset price booms significantly predict Δ CoVaR. We also provide out-of-sample forecasts of a countercyclical, forward-looking measure of systemic risk, and show that the 2006:IV value of this measure would have predicted more than one-third of realized Δ CoVaR during the 2007–2009 financial crisis. (JEL C58, E32, G01, G12, G17, G20, G32)

This paper estimates the productivity gains from reducing tariffs on final goods and from reducing tariffs on intermediate inputs. Lower output tariffs can increase productivity by inducing tougher import competition, whereas cheaper imported inputs can raise productivity via learning, variety, and quality effects. We use Indonesian manufacturing census data from 1991 to 2001, which include plant-level information on imported inputs. The results show that a 10 percentage point fall in input tariffs leads to a productivity gain of 12 percent for firms that import their inputs, at least twice as high as any gains from reducing output tariffs. (JEL F12, F13, L16, O14, O19, O24)

Output Fluctuations in the United States: What Has Changed since the Early 1980's? by Margaret M. McConnell and Gabriel Perez-Quiros. Published in volume 90, issue 5, pages 1464-1476 of American Economic Review, December 2000

This paper provides evidence that financial markets can directly affect economic growth by studying the relaxation of bank branch restrictions in the United States. We find that the rates of real, per capita growth in income and output increase significantly following intrastate branch reform. We also argue that the observed changes in growth are the result of changes in the banking system. Improvements in the quality of bank lending, not increased volume of bank lending, appear to be responsible for faster growth.

The evaluation of numerous school reforms requires an understanding of the value of better schools. Given the difficulty of calculating the relationship between school quality and student outcomes, I turn to another method and use house prices to infer the value parents place on school quality. I look within school districts at houses located on attendance district boundaries; houses then differ only by the elementary school the child attends. I thereby effectively remove the variation in neighborhoods, taxes, and school spending. I find that parents are willing to pay 2.5 percent more for a 5 percent increase in test scores. This finding is robust to a number of sensitivity checks.

This article designs a framework for evaluating the causes, consequences, and future implications of financial services industry consolidation, reviews the extant research literature within the context of this framework (over 250 references), and suggests fruitful avenues for future research. The evidence is consistent with increases in market power from some types of consolidation; improvements in profit efficiency and diversification of risks, but little or no cost efficiency improvement on average; relatively little effect on the availability of services to small customers; potential improvements in payments system efficiency; and potential costs on the financial system from increases in systemic risk or expansion of the financial safety net.

This paper explores the ability of conditional versions of the CAPM and the consumption CAPMjointly the (C)CAPMto explain the cross section of average stock returns. Central to our approach is the use of the log consumptionwealth ratio as a conditioning variable. We demonstrate that such conditional models perform far better than unconditional specifications and about as well as the Fama-French three-factor model on portfolios sorted by size and book-to-market characteristics. The conditional consumption CAPM can account for the difference in returns between low-book-to-market and high-book-to-market portfolios and exhibits little evidence of residual size or book-to-market effects.

This paper examines the underpinnings of the successful performance of the US economy in the late 1990s. Relative to the early 1990s, output growth has accelerated by nearly two percentage points. We attribute this to rapid capital accumulation, a surge in hours worked, and faster growth of total factor productivity. The acceleration of productivity growth, driven by information technology, is the most remarkable feature of the US growth resurgence. We consider the implications of these developments for the future growth of the US economy.

Financial institutions such as banks are ultimately exposed to macroeconomic fluctuations I the countries to which they have exposure, the most acute example being commercial lending to companies whose fortunes fluctuate with aggregate demand. This risk management need for financial institutions motivated us to build a compact global macroeconomic model capable of generating (point as well as density) forecasts for a core set of macroeconomic factors for a set of regions and countries which explicitly allows for interconnections and interdependencies that exist between national and international factors. This paper provides such a global modeling framework; making use of recent advances in the analysis of cointegrating systems. In an unrestricted VAR(p) model in k endogenous variables covering N countries, the number of unknown parameters will be unfeasibly large, of order p(kN-1), requiring a more parsimonious model specification. We first estimate individual country/region specific vector error correcting models, where the domestic macroeconomic variables are related to corresponding foreign variable constructed exclusively to match the international trade pattern of the country under consideration. The individual country models are then combined in a consistent and cohesive manner to generate forecasts for all the variables in the world economy simultaneously. We estimate the model for 26 countries grouped into 11 regions using quarterly data from 1970Q1 to 1999Q1 and shed light on the degree of regional interdependencies by investigating the time profile of the transmission of shocks to one variable in a given country/region to the rest of the world. We then use the estimated global model as the economic engine for generating a conditional loss distribution of a credit portfolio and illustrate the effects of various global risk scenarios on the loss distribution.

The striking growth in the trade share of output is one of the most important developments in the world economy since World War II. Two features of this growth present challenges to the standard trade models. First, the growth is generally thought to have been generated by falling tariff barriers worldwide. But tariff barriers have decreased by only about 11 percentage points since the early 1960s; the standard models cannot explain the growth of trade without assuming counterfactually large elasticities of substitution between goods. Second, tariff declines were much larger prior to the mid 1980s than after, and yet, trade growth was smaller in the earlier period than in the later period. The standard models have difficulty generating this nonlinear feature. This paper develops a two-country dynamic Ricardian trade model that offers a resolution of these two puzzles. The key idea embedded in this model is vertical specialization, which occurs when countries specialize only in particular stages of a good's production sequence. The model generates a nonlinear trade response to tariff reductions and can explain over 50 percent of the growth of trade. Finally, the model has important implications for the gains from trade.

In recent years, a number of industrialized countries have adopted a strategy for monetary policy known as ‘inflation targeting.’ The authors describe how this approach has been implemented in practice and argue that it is best understood as a broad framework for policy, which allows the central bank ‘constrained discretion,’ rather than as an ironclad policy rule in the Friedman sense. They discuss the potential of the inflation-targeting approach for making monetary policy more coherent and transparent and for increasing monetary policy discipline. The authors' final section addresses some additional practical issues raised by this approach.

This paper examines the out-of-sample performance of various financial variables as predictors of U.S. recessions. Series such as interest rates and spreads, stock prices, and monetary aggregates are evaluated individually and in comparison with other financial and nonfinancial indicators. The analysis focuses on out-of-sample performance from one to eight quarters ahead. Results show that stock prices are useful with one- to three-quarter horizons, as are some well-known macroeconomic indicators. Beyond one quarter, however, the slope of the yield curve emerges as the clear individual choice and typically performs better by itself out of sample than in conjunction with other variables.

The pattern of disagreement between bond raters suggests that banks and insurance firms are inherently more opaque than other types of firms. Moody's and S&P split more often over these financial intermediaries, and the splits are more lopsided, as theory here predicts. Uncertainty over the banks stems from certain assets, loans and trading assets in particular, the risks of which are hard to observe or easy to change. Banks' high leverage, which invites agency problems, compounds the uncertainty over their assets. These findings bear on both the existence and reform of bank regulation.

Technology-based (“FinTech”) lenders increased their market share of U.S. mortgage lending from 2% to 8% from 2010 to 2016. Using loan-level data on mortgage applications and originations, we show that FinTech lenders process mortgage applications 20% faster than other lenders, controlling for observable characteristics. Faster processing does not come at the cost of higher defaults. FinTech lenders adjust supply more elastically than do other lenders in response to exogenous mortgage demand shocks. In areas with more FinTech lending, borrowers refinance more, especially when it is in their interest. We find no evidence that FinTech lenders target borrowers with low access to finance.Received June 1, 2017; editorial decision November 5, 2018 by Editor Wei Jiang. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

How does one tell when rapid growth in house prices is caused by fundamental factors of supply and demand and when it is an unsustainable bubble? In this paper, we explain how to assess the state of house prices—both whether there is a bubble and what underlying factors support housing demand—in a way that is grounded in economic theory. In doing so, we correct four common fallacies about the costliness of the housing market. For a number of reasons, conventional metrics for assessing pricing in the housing market such as price-to-rent ratios or price-to-income ratios generally fail to reflect accurately the state of housing costs. To the eyes of analysts employing such measures, housing markets can appear “exuberant” even when houses are in fact reasonably priced. We construct a measure for evaluating the cost of home owning that is standard for economists—the imputed annual rental cost of owning a home, a variant of the user cost of housing—and apply it to 25 years of history across a wide variety of housing markets. This calculation enables us to estimate the time pattern of housing costs within a market. As of the end of 2004, our analysis reveals little evidence of a housing bubble.

Understanding of monetary transmission mechanisms is crucial to answering a broad range of questions. These transmission mechanisms include interest-rate effects, exchange-rate effects, other asset price effects, and the so-called credit channel. This introduction to the symposium provides an overview of the main types of monetary transmission mechanisms found in the literature and a perspective on how the papers in the symposium relate to the overall literature and to each other.

ABSTRACT This paper tests how competition in local U.S. banking markets affects the market structure of nonfinancial sectors. Theory offers competing hypotheses about how competition ought to influence firm entry and access to bank credit by mature firms. The empirical evidence, however, strongly supports the idea that in markets with concentrated banking, potential entrants face greater difficulty gaining access to credit than in markets in which banking is more competitive.