We study the competitive equilibrium of large random economies with linear activities using methods of statistical mechanics. We focus on economies with C commodities, N firms, each running a randomly drawn linear technology, and one consumer. We derive, in the limit N, C ∞ with n=N/C fixed, a complete description of the statistical properties of typical equilibria. We find two regimes, which in the limit of efficient technologies are separated by a phase transition, and argue that endogenous technological change drives the economy close to the critical point.

We develop a dynamic general equilibrium growth model, where households purchase final goods on cash or credit and have different capital and money endowments, to investigate whether inflation affects trends in income and consumption inequality. We show that, under a strong substitutability between cash and credit goods, inflation has a negative relationship with income inequality, but a U-shaped relationship with consumption inequality. The divergence between income and consumption inequality explains several recent empirical observations. This result has important policy implications, as consumption inequality better reflects the welfare distribution whereas income inequality fails to capture consumption disparities resulting from different consumption and asset distributions across households. In the growth model with heterogeneous households, there is a mixed relationship between growth and income inequality, confirming the existence of the Kuznets curve. The inflation-driven asset reallocation might also produce a Mundell–Tobin effect, enhancing growth.

This paper constructs a quantitative general equilibrium life-cycle model with uninsurable labor income to account for the differences in wealth accumulation and homeownership between Korea and the United States. The model incorporates different structures in the housing market in the two countries, namely, the mortgage market and the rental arrangements. The results from the calibrated model quantitatively explain some empirical findings in the aggregate and life-cycle profiles of wealth and homeownership. Quantitative policy experiments show that the mortgage market alone can account for more than 40% of the differences in the aggregate homeownership ratios. When coupled with the rental arrangements, both institutions can account for approximately 52% of the differences in the cross-country homeownership ratios.

We analyze the forecasting performance of small mixed-frequency factor models when the observed variables share stochastic trends. The indicators are observed at various frequencies and are tied together by cointegration so that valuable high-frequency information is passed to low-frequency series through the common factors. Differencing the data breaks the cointegrating link among the series and some of the signal leaks out to the idiosyncratic components, which do not contribute to the transfer of information among indicators. We find that allowing for common trends improves forecasting performance over a stationary factor model based on differenced data. The “common-trends factor model” outperforms the stationary factor model at all analyzed forecast horizons. Our results demonstrate that when mixed-frequency variables are cointegrated, modeling common stochastic trends improves forecasts.

A nonlinear programming formulation is introduced to solve infinite-horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to approximate value functions. Our numerical results show that this nonlinear programming is efficient and accurate, and avoids inefficient discretization.

In this paper, we analyze the adequacy of using GARCH as the data-generating process to model conditional volatility of stock market index rates-of-return series. Using the Hinich portmanteau bicorrelation test, we find that a GARCH formulation or any of its variants fail to provide an adequate characterization for the underlying process of the main Latin American stock market indices. Policymakers need to be careful when using autoregressive models for policy analysis and forecast because the inadequacy of GARCH models has strong implications for the pricing of stock index options, portfolio selection, and risk management. In particular, measures of spillover effects and output volatility may not be correct when GARCH-type models are used to evaluate economic policy.

This paper develops a model that endogenizes both directed technologies and demography. Potential innovators decide which technologies to develop after considering available factors of production, and individuals decide the quality and quantity of their children after considering available technologies. This interaction allows us to evaluate potentially divergent development paths. We find that unskilled labor–biased technological growth can induce higher fertility and lower education, exerting downward pressure on growth in per-person income. Despite this, for most plausible developing-country scenarios, unskilled intensive growth produces more per-person income than skill-intensive growth. This result is robust to a variety of growth modeling assumptions.

In this article, we show how tests of nonlinear serial dependence can be applied to high-frequency time series data that exhibit high volatility, strong mean reversion, and leptokurtotis. Portmanteau correlation, bicorrelation, and tricorrelation tests are used to detect nonlinear serial dependence in the data. Trimming is used to control for the presence of outliers in the data. The data that are employed are 161,786 half-hourly spot electricity price observations recorded over nearly a decade in the wholesale electricity market in New South Wales, Australia. Strong evidence of nonlinear serial dependence is found and its implications for time series modeling are discussed.

Using a structural vector autoregressive (SVAR) model, this paper provides deeper insight into unemployment dynamics in Germany. We identify a technology shock and two policy shocks that play a central role in business cycle research. Accordingly, we enrich the discussion on the sources of unemployment dynamics by considering demand-side impulses. The worker reallocation process varies substantially with the identified shocks. The job-finding rate plays a larger role after a technology shock and a monetary policy shock, whereas the separation rate appears to be the dominant margin after a fiscal policy shock. Technology shocks turn out to be relatively important for variations in the transition rates. Regarding policy shocks, our results point toward fiscal interventions as a promising instrument but with several limitations.

Stochastic models with economywide shocks imply that the welfare costs of aggregate volatility are negligible. Empirical evidence suggests that the volatility of idiosyncratic shocks is several times that of aggregate shocks. This paper introduces both types of shocks. We find that if in the process of eliminating aggregate risk the policymaker can reduce idiosyncratic risk by an amount suggested by available empirical evidence, the welfare gains from stabilization can become significant. The introduction of idiosyncratic risk has important implications for asset pricing, and in particular may reduce the risk-free rate substantially, through the precautionary savings motive. Many of our results are sensitive both to the degree of risk aversion and to the flexibility of labor supply. The paper highlights the trade-offs involved in analyzing the effects of risk on growth and welfare and on asset pricing, clarifying the need to examine these issues within a unified stochastic general equilibrium framework.

The empirical importance of news shocks—anticipated future shocks—in business cycle fluctuations has been explored by using only actual data when estimating models augmented with news shocks. This paper additionally exploits forecast data to identify news shocks in a canonical dynamic stochastic general equilibrium model. The estimated model shows new empirical evidence that technology news shocks are a major source of fluctuations in US output growth. Exploiting the forecast data not only generates more precise estimates of news shocks and other parameters in the model, but also increases the contribution of technology news shocks to the fluctuations.

We investigate whether recoveries following normal recessions differ from recoveries following recessions that are associated with either banking crises or housing crises. Using a parametric panel framework that allows for a bounce-back in the level of output during the recovery, we find that normal recessions are followed by strong recoveries in advanced economies. This bounce-back is absent following recessions associated with banking crises and housing crises. Consequently, the permanent output losses of recessions associated with banking crises and housing crises are considerably larger than those of normal recessions.

In this paper, we investigate the importance of aggregate fluctuations for the assessment of the optimal level of public debt in an incomplete-markets economy. We start by building a steady state model in which households are only subject to uninsurable idiosyncratic risk and evaluate the optimal level of public debt. We then augment the model to allow for aggregate risk and measure the impact on the optimal level. We show that the cyclical behavior of the economy has a quantitative impact on this level that can be decomposed into the effects of the aggregate productivity shock and the cyclicality of unemployment. Moreover, we find that matching wealth distribution statistics substantially changes the optimal level of public debt.

This paper develops a bank model to study supply-driven contractions in credit or credit crunches. In the model, the bank is affected by financial frictions in raising external funds. These frictions imply that the bank repairs its balance sheet only gradually following a negative shock that weakens the bank's capital position. Consequently, there is persistency in the response of bank lending even when the original shock (productivity or interest rate) is i.i.d. The nonlinear nature of these financial frictions also generates (i) a precautionary motive even with risk-neutral shareholders: the bank increases its desired level of capital if risk increases; (ii) an asymmetric response of lending: negative disturbances can have a bigger impact than positive ones; and (iii) volatility clustering in risk spreads and the bank's share price.

The recent financial crisis highlighted the limits of the originate to distribute model of banking, but its nexus with the macroeconomy remains unexplored. I build a business cycle model with banks engaging in credit risk transfer (CRT) under informational externalities. Markets for CRT provide liquidity insurance to banks, but the emergence of a pooling equilibrium can also impair the banks' monitoring incentives. In normal times and in face of standard macro shocks the insurance benefits of CRT prevail and the business cycle is stabilized. In face of financial/liquidity shocks the extent of informational asymmetries is larger and the business cycle is amplified. The macro model with CRT can also reproduce well a number of macro and banking statistics over the period of rapid growth of this banks' business model.

This paper is the introduction to the Macroeconomic Dynamics Special Issue on Measurement with Theory. The Guest Editors of the special issue are William A. Barnett, W. Erwin Diewert, Shigeru Iwata, and Arnold Zellner. The papers included are part of a larger initiative to promote measurement with theory in economics.

The Ramsey optimal taxation theory implies that the tax rate on capital income should be zero in the long run. This result holds even if the social planner only cares about workers that do not hold assets, or if the planner only cares about any other group in the economy. This paper demonstrates that although all households agree that capital income taxation should be eliminated in the long run, they do not agree on how to eliminate these taxes. Wealthy households would prefer a reform that is funded by higher taxes on labor income, whereas households with little wealth would prefer a reform that is funded mostly by high taxes on initial wealth. Pareto-improving reforms typically exist, but the welfare gains of such reforms are modest.

This paper explores the influence of wage and price staggering on monetary persistence. We show that, for plausible parameter values, wage and price staggering are complementary in generating monetary persistence. We do so by proposing the new measure of “quantitative inertia,” after discussing weaknesses of the “contract multiplier,” a standard measure of monetary persistence. The existence of complementarities means that beyond understanding how wage and price staggering work in isolation, it is important to investigate their interactions. Furthermore, our analysis indicates that the degree of monetary persistence generated by wage vis-à-vis price staggering depends on the relative competitiveness of the labor and product markets. We show that the conventional finding that wage staggering generates more persistence than price staggering holds under homogeneous capital accumulation. Under firm-specific capital, wage staggering generates more persistence only when the labor market is sufficiently competitive relative to the product market.

Prior to the financial crisis, mainstream monetary policy practice had become disconnected from money. We outline the basic rationale for this development using a simple model of money and credit in which we explore the conditions under which money matters directly for the conduct of policy. Then, using a DSGE model, we examine the circumstances under which money becomes more closely linked to inflation. We find that money matters when the variance of the supply of lending dominates productivity and the velocity of money demand. This is because amplifying the role of loans supply leads to an expansion in aggregate demand, via a compression of the external finance premium, which is inflationary. We consider a number of alternative monetary policy rules, and find that a rule which exploits the joint information from money and the external finance premium performs best.

In this study I bring together two different literatures: the hierarchical education literature and the skill-biased growth literature. In an overlapping-generations model I introduce capital–skill complementarity into a hierarchical education system. I obtain results that differ qualitatively from previous studies, among which are the following: (i) At earlier stages of development, basically educated labor contributes to growth more than highly educated labor. The opposite occurs at later stages. (ii) Even when all individuals acquire higher education, a growth-enhancing policy subsidizes higher education. (iii) In a growth-enhancing policy, the share of public resources allocated to basic education declines as the economy grows. (iv) The enrollment rate evolves in an S-shaped pattern, as occurred in several OECD countries.