Federal Reserve Bank of St. Louis

Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the predictive ability of technical indicators with that of macroeconomic variables. Technical indicators display statistically and economically significant in-sample and out-of-sample predictive power, matching or exceeding that of macroeconomic variables. Furthermore, technical indicators and macroeconomic variables provide complementary information over the business cycle: technical indicators better detect the typical decline in the equity risk premium near business-cycle peaks, whereas macroeconomic variables more readily pick up the typical rise in the equity risk premium near cyclical troughs. Consistent with this behavior, we show that combining information from both technical indicators and macroeconomic variables significantly improves equity risk premium forecasts versus using either type of information alone. Overall, the substantial countercyclical fluctuations in the equity risk premium appear well captured by the combined information in technical indicators and macroeconomic variables. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2013.1838 . This paper was accepted by Wei Jiang, finance.

We develop a quantitative framework to explain the relationship between aggregate/sector-level total factor productivity (TFP) and financial development across countries. Financial frictions distort the allocation of capital and entrepreneurial talent across production units, adversely affecting measured productivity. In our model, sectors with larger scales of operation (e.g., manufacturing) have more financing needs, and are hence disproportionately vulnerable to financial frictions. Our quantitative analysis shows that financial frictions account for a substantial part of the observed cross-country differences in output per worker, aggregate TFP, sector-level relative productivity, and capital-to-output ratios. (JEL E23, E44, O41, O47)

We propose that a simple "dual-self" model gives a unified explanation for several empirical regularities, including the apparent time inconsistency that has motivated models of quasi-hyperbolic discounting and Rabin’s paradox of risk aversion in the large and small. The model also implies that self-control costs imply excess delay, as in the O'Donoghue and Rabin models of quasi-hyperbolic utility, and it explains experimental evidence that increased cognitive load makes temptations harder to resist. The base version of our model is consistent with the Gul-Pesendorfer axioms, but we argue that these axioms must be relaxed to account for the effect of cognitive load.

This article describes a large, monthly frequency, macroeconomic database with the goal of establishing a convenient starting point for empirical analysis that requires “big data.” The dataset mimics the coverage of those already used in the literature but has three appealing features. First, it is designed to be updated monthly using the Federal Reserve Economic Data (FRED) database. Second, it will be publicly accessible, facilitating comparison of related research and replication of empirical work. Third, it will relieve researchers from having to manage data changes and revisions. We show that factors extracted from our dataset share the same predictive content as those based on various vintages of the so-called Stock–Watson dataset. In addition, we suggest that diffusion indexes constructed as the partial sum of the factor estimates can potentially be useful for the study of business cycle chronology. Supplementary materials for this article are available online.

Our paper assesses progress made by the profession in understanding whether and how exchange rate intervention works. We review theory and evidence on official intervention, concentrating primarily on work published in the last decade or so. We conclude that, unlike the profession's consensus of the 1980s, official intervention can be effective, especially as a signal of policy intentions and when publicly announced and concerted. We note an apparent empirical puzzle concerning the secrecy of much intervention and suggest another way for intervention to be effective which has received little attention in the literature, namely by remedying a coordination failure in the foreign exchange market.

This paper seeks to identify the characteristics that make individual U.S. banks more likely to fail or be acquired. We use bank-specific information to estimate competing-risks hazard models with time-varying covariates. We use alternative measures of productive efficiency to proxy management quality, and find that inefficiency increases the risk of failure while reducing the probability of a bank's being acquired. Finally, we show that the closer to insolvency a bank is (as reflected by a low equity-to-assets ratio) the more likely is its acquisition.

Substances cross the blood-brain barrier (BBB) by a variety of mechanisms. These include transmembrane diffusion, saturable transporters, adsorptive endocytosis, and the extracellular pathways. Here, we focus on the chief characteristics of two mechanisms especially important in drug delivery: transmembrane diffusion and transporters. Transmembrane diffusion is non-saturable and depends, on first analysis, on the physicochemical characteristics of the substance. However, brain-to-blood efflux systems, enzymatic activity, plasma protein binding, and cerebral blood flow can greatly alter the amount of the substance crossing the BBB. Transport systems increase uptake of ligands by roughly 10-fold and are modified by physiological events and disease states. Most drugs in clinical use to date are small, lipid soluble molecules that cross the BBB by transmembrane diffusion. However, many drug delivery strategies in development target peptides, regulatory proteins, oligonucleotides, glycoproteins, and enzymes for which transporters have been described in recent years. We discuss two examples of drug delivery for newly discovered transporters: that for phosphorothioate oligonucleotides and for enzymes.

Christopher Neely, Paul Weller, Rob Dittmar, Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach, The Journal of Financial and Quantitative Analysis, Vol. 32, No. 4 (Dec., 1997), pp. 405-426

We develop a dynamic trade model with spatially distinct labor markets facing varying exposure to international trade. The model captures the role of labor mobility frictions, goods mobility frictions, geographic factors, and input‐output linkages in determining equilibrium allocations. We show how to solve the equilibrium of the model and take the model to the data without assuming that the economy is at a steady state and without estimating productivities, migration frictions, or trade costs, which can be difficult to identify. We calibrate the model to 22 sectors, 38 countries, and 50 U.S. states. We study how the rise in China's trade for the period 2000 to 2007 impacted U.S. households across more than a thousand U.S. labor markets distinguished by sector and state. We find that the China trade shock resulted in a reduction of about 0.55 million U.S. manufacturing jobs, about 16% of the observed decline in manufacturing employment from 2000 to 2007. The U.S. gains in the aggregate, but due to trade and migration frictions, the welfare and employment effects vary across U.S. labor markets. Estimated transition costs to the new long‐run equilibrium are also heterogeneous and reflect the importance of accounting for labor dynamics.

The term decentralized finance (DeFi) refers to an alternative financial infrastructure built on top of the Ethereum blockchain. DeFi uses smart contracts to create protocols that replicate existing financial services in a more open, interoperable, and transparent way. This article highlights opportunities and potential risks of the DeFi ecosystem. I propose a multi-layered framework to analyze the implicit architecture and the various DeFi building blocks, including token standards, decentralized exchanges, decentralized debt markets, blockchain derivatives, and on-chain asset management protocols.

ABSTRACT We study portfolio choice when labor income and dividends are cointegrated. Economically plausible calibrations suggest young investors should take substantial short positions in the stock market. Because of cointegration the young agent's human capital effectively becomes “stock‐like.” However, for older agents with shorter times‐to‐retirement, cointegration does not have sufficient time to act, and thus their human capital becomes more “bond‐like.” Together, these effects create hump‐shaped life‐cycle portfolio holdings, consistent with empirical observation. These results hold even when asset return predictability is accounted for.

We quantitatively analyze the role of financial frictions and resource misallocation in explaining development dynamics. Our model economy with financial frictions converges to the new steady state slowly after a reform triggers efficient reallocation of resources; the transition speed is half that of the conventional neoclassical model. Furthermore, in the model economy, investment rates and total factor productivity are initially low and increase over time. We present data from the so-called miracle economies on the evolution of macro aggregates, factor reallocation, and establishment size distribution that support the aggregate and micro-level implications of our theory.

We find that presidential and congressional influences affect the rate of disaster declaration and the allocation of FEMA disaster expenditures across states. States politically important to the president have a higher rate of disaster declaration by the president, and disaster expenditures are higher in states having congressional representation on FEMA oversight committees. Election year impacts are also found. Our models predict that nearly half of all disaster relief is motivated politically rather than by need. The findings reject a purely altruistic model of FEMA assistance and question the relative effectiveness of government versus private disaster relief.

This paper investigates the international asset allocation effects of time-variations in higher-order moments of stock returns such as skewness and kurtosis. In the context of a four-moment International Capital Asset Pricing Model (ICAPM) specification that relates stock returns in five regions to returns on a global market portfolio and allows for time-varying prices of covariance, co-skewness, and co-kurtosis risk, we find evidence of distinct bull and bear regimes. Ignoring such regimes, an unhedged US investor's optimal portfolio is strongly diversified internationally. The presence of regimes in the return distribution leads to a substantial increase in the investor's optimal holdings of US stocks, as does the introduction of skewness and kurtosis preferences.

The case against patents can be summarized briefly: there is no empirical evidence that they serve to increase innovation and productivity, unless productivity is identified with the number of patents awarded—which, as evidence shows, has no correlation with measured productivity. Both theory and evidence suggest that while patents can have a partial equilibrium effect of improving incentives to invent, the general equilibrium effect on innovation can be negative. A properly designed patent system might serve to increase innovation at a certain time and place. Unfortunately, the political economy of government-operated patent systems indicates that such systems are susceptible to pressures that cause the ill effects of patents to grow over time. Our preferred policy solution is to abolish patents entirely and to find other legislative instruments, less open to lobbying and rent seeking, to foster innovation when there is clear evidence that laissez-faire undersupplies it. However, if that policy change seems too large to swallow, we discuss in the conclusion a set of partial reforms that could be implemented

This article introduces four models of conditional heteroscedasticity that contain Markov-switching parameters to examine their multiperiod stock-market volatility forecasts as predictions of options-implied volatilities. The volatility model that best predicts the behavior of the options-implied volatilities allows the Student-t degrees-of-freedom parameter to switch such that the conditional variance and kurtosis are subject to discrete shifts. The half-life of the most leptokurtic state is estimated to be a week, so expected market volatility reverts to near-normal levels fairly quickly following a spike.

Abstract This paper investigates how a central bank digital currency can be expected to impact a monopolistic banking sector. The paper’s framework of analysis combines the Diamond (1965) model of government debt with the Klein (1971) and Monti (1972) model of a monopoly bank. The paper finds that the introduction of a central bank digital currency has no detrimental effect on bank lending activity and may, in some circumstances, even serve to promote it. Competitive pressure leads to a higher monopoly deposit rate which reduces profit but expands deposit funding through greater financial inclusion and desired saving. An appeal to available theory and evidence suggests that a properly designed central bank digital currency is not likely to threaten financial stability.

A key question that has arisen during recent debates is whether government spending multipliers are larger during times when resources are idle. This paper seeks to shed light on this question by analyzing new quarterly historical data covering multiple large wars and depressions in the United States and Canada. Using Jorda's (2005) method for estimating impulse responses, we find no evidence that multipliers are greater during periods of high unemployment in the United States. In every case, they are below unity. We do find evidence of higher multipliers during periods of slack in Canada, with some multipliers above unity.

We reevaluate the role of human capital in determining the wealth of nations. We use standard human capital theory to estimate stocks of human capital and allow the quality of human capital to vary across countries. Our model can explain differences in schooling and earnings profiles and, consequently, estimates of Mincerian rates of return across countries. We find that effective human capital per worker varies substantially across countries. Cross-country differences in Total Factor Productivity (TFP) are significantly smaller than found in previous studies. Our model implies that output per worker is highly responsive to changes in TFP and demographic variables.

Foreign direct investment (FDI) began to flow into China with advent of reforms in 1978. Following a period of relatively slow growth, FDI inflows to China picked up after 1990, as China surpassed every other nation but the United States in attracting foreign investment. In particular, coastal regions of China have received the bulk of FDI inflows to the country. In this paper, we use province-level data to explain the pattern of FDI location across China. We build upon previous research, introducing new potential determinants, using more recent FDI data, and incorporating spatial econometric techniques. In doing so, we test for potential econometric problems arising from the spatial pattern of the data, and correct for them by running more appropriate models. We find that economic size, labor productivity and coastal location attract FDI, while higher wages and illiteracy rates deter it. The transportation infrastructure variables we try are not found to have statistically significant relationships with the level of FDI inflows across provinces.