The Great Moderation is characterized as a period of stable macroeconomic conditions, especially with regard to inflation. Under the sticky information theory, this environment may provide a few incentives for agents to update information on inflation, thus, producing a new slope of the sticky information Phillips curve. We estimate the degree of information rigidity implied by the sticky information Phillips curve. Using threshold models, we identify two regimes of high and low inflation, finding that each identified regime is associated with a specific degree of information stickiness. This evidence is consistent with agents that update information faster when inflation is higher.

This paper investigates conditions under which a long-run recursive model can be used to identify a structure. Economists frequently employ this type of empirical model. I define the class of long-run partially recursive structures. If an economic system is a member of this class, then certain long-run recursive empirical models will obtain some of the structural impulse response functions. This sufficient condition for a structure is first shown in a vector autoregression. A well-known example from the literature is used to illustrate this particular class of structures and to present some useful applications of the result. Then the result is shown in models of cointegrated time series. Necessary conditions for a long-run recursive model to identify structure are addressed in the conclusion.

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.

Gold is a globally traded asset and held in large quantities by investors and central banks. Since there is no established model to assess whether the price of gold is overvalued or undervalued, we propose a relative valuation framework based on gold price ratios. This idea is not confined to gold but offers the foundation for relative valuation of a broad range of different assets or asset classes. We analyze gold prices relative to commodity prices, consumer prices, stock prices, dividend, and bond yields and find that the relative value of gold varies significantly over time. An analysis of the factors which drive these variations demonstrates that inflation expectations and uncertainty have a strong influence on gold ratios while macroeconomic fundamentals are less important. More specifically, a boost in confidence decreases the relative price of gold while heightened uncertainty increases the relative price of gold, which confirms the role of gold as a safe haven.

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.

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.

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.

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.

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.

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.

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 development of artificial intelligence (AI) does influence human jobs but not necessarily in a negative way. Although labor force participation rates and firms’ job vacancies for human labor decline, the unemployment rate may be lower than that in an economy without AI. In an economy with heterogeneously skilled workers, the invention of AI usually has a negative effect on the skilled labor market but a positive effect on the unskilled labor market. The overall unemployment rate may decline as AI develops.

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 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 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 studies the evolution of wealth inequality in an economy with endogenous borrowing constraints. In the model economy, young agents need to borrow to finance human capital investments but cannot commit to repaying their loans. Creditors can punish defaulters by banishing them permanently from the credit market. At equilibrium, loan default is prevented by imposing a borrowing limit tied to the borrower's inheritance. The heterogeneity in inheritances translates into heterogeneity in borrowing limits: endogenously, some borrowers face a zero borrowing limit, and some are partly constrained, whereas others are unconstrained. Depending on the initial distribution of inheritances, it is possible that all lineages are attracted either to the zero-borrowing-limit steady state or to the unconstrained-borrowing steady state—long-run equality. It is also possible that some lineages end up in one steady state and the rest in the other—complete polarization.

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 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.

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.