This study introduces automation into a Schumpeterian growth model to explore the effects of R&D and automation subsidies. R&D subsidy increases innovation and growth but decreases the share of automated industries and the degree of capital intensity in the aggregate production function. Automation subsidy has the opposite effects on these macroeconomic variables. Calibrating the model to US data, we find that raising R&D subsidy increases the welfare of high-skill workers but decreases the welfare of low-skill workers and capital owners, whereas increasing automation subsidy increases the welfare of high-skill workers and capital owners but decreases the welfare of low-skill workers. Therefore, whether the government should subsidize innovation or automation depends on how it evaluates the welfare gains and losses of different agents in the economy.

There is no consensus on the existence of welfare gains from international monetary policy cooperation. This study adds to the debate by providing a new open macroeconomics model with incomplete exchange rate pass-through. We find that, from a global perspective, the welfare gains from international monetary policy cooperation arise with incomplete exchange rate pass-through. Furthermore, the country’s incentive for cooperation increases with its degree of exchange rate pass-through. Cooperation benefits small countries with high pass-through; however, it is disadvantageous to large countries with low pass-through. In addition, when there is in the absence of cooperation, fixed exchange rate regime is preferred for a country suffering from monetary uncertainty, particularly for small economies with high exchange rate pass-through.

This study investigates the labor market under increased automation of middle-skilled jobs wherein worker suitability for these jobs is considered. We examine two effects of increased automation on workers. The first effect is the possibility of replacement of middle-skilled workers by machines. The second effect is the diversity in job mismatch probabilities of workers. If machines perform a worker’s suitable jobs more (or less) than the worker’s unsuitable jobs, then the worker’s job mismatch probability rises (or declines). Because workers who have larger job mismatch probabilities remain job seekers, it is more difficult for a firm to find a suitable worker. Due to these two effects, underemployment rises.

This paper offers a framework for measuring global growth and inflation, built on standard index number theory, national accounts principles, and the concepts and methods for international macro-economic comparisons. Our approach provides a sound basis for purchasing power parity (PPP)- and exchange rate (XR)-based global growth and inflation measures. The Sato–Vartia index number system advocated here offers very similar results to a Fisher system but has the added advantage of allowing a complete decomposition with PPP or XR effects. For illustrative purposes, we present estimates of global growth and inflation for 141 countries over the years 2005 and 2011. The contribution of movements in XRs and PPPs to global inflation are presented. The aggregation properties of the method are also discussed.

This paper provides a closed-form solution to a standard asset pricing model with habit formation when the growth rate of endowment follows a first-order Gaussian autoregressive process. We determine conditions that guarantee the existence of a stationary bounded equilibrium. The findings are useful because they allow to evaluate the accuracy of various approximation methods to nonlinear rational expectation models. Furthermore, they can be used to perform simulation experiments to study the finite sample properties of various estimation methods.

An estimated Markov-switching DSGE modeling framework that allows for parameter shifts across regimes is employed to test the hypothesis of regime-dependent credibility of Hong Kong's linked exchange rate system. The baseline model distinguishes two regimes with respect to the time-series properties of the risk premium. Regime-dependent impulse responses to macroeconomic shocks reveal substantial differences in spreads. To test the sensitivity of the results, a number of robustness checks are performed. The findings contribute to efforts at modeling exchange rate regime credibility as a nonlinear process with two distinct regimes.

This paper develops a theory of human capital to investigate the role of early childhood health in explaining the large and persistent schooling gaps observed within and across countries. Quantitative analysis using the theory and data from 98 countries shows that early health inequalities within developingcountries strongly amplify later schooling gaps— counterfactually eliminating inequalities reduces schooling Ginis by an average of 18% in developing economies but has only mild effects in richer countries. Moreover, early health inequalities are found to be an important source of schooling variation across countries— universally equating early health to the average US level reduces the cross-country standard deviation of average schooling attainment by over 40%. Additional policy experiments reveal that the gains from early health interventions tend to be amplified by later educational investments in developing economies, while those targeting school-aged children may be limited if early health conditions are ignored.

Growth in total factor productivity (TFP) in the USA has slowed down significantly since the mid-2000s, reminiscent of the productivity slowdown of the 1970s. This paper investigates the implications of a productivity slowdown on macroeconomic variables using a standard real business cycle (RBC) model, extended with regime-switching in trend productivity growth and Bayesian learning regarding the growth regime. I estimate the Markov-switching parameters using US data and maximum-likelihood methods, and compute the model solution using global projection methods. Simulations reveal that, while adding a regime-switching component to the standard RBC setup increases the volatility in the system, further incorporating incomplete information and learning significantly dampens this effect. The dampening is mainly due to the responses of investment and labor in response to a switch in the trend component of TFP growth, which are weaker in the incomplete information case as agents mistakenly place some probability that the observed decline in TFP growth is due to the transient component and not due to a regime switch. The model offers an objective way to infer slowdowns in trend productivity, and suggests that macroeconomic aggregates in the USA are currently close to their potential levels given observed productivity, while counterfactual simulations indicate that the cost of the productivity slowdown to US welfare has been significant.

We develop a model with financial frictions and sovereign default risk wherein the maturity of public debt is allowed to be larger than one period. When the debt portfolio has longer average maturities, public debt increases less in the event of a crisis, reducing the size of the subsequent fiscal consolidation through distorsionary taxes or public spending, with positive effects on welfare. In addition, we provide some results suggesting that optimized fiscal responses to a crisis depend on the average maturity of the debt portfolio.

This paper shows how fiscal policy affects unemployment in a New Keynesian model with search and matching frictions and distortionary taxation. The model is estimated using US data that includes labor market flows and distinct fiscal instruments. Several findings stand out. First, unemployment multipliers for spending and consumption tax cuts are substantial, even though output multipliers turn out to be less than one. Second, multipliers for labor tax cuts are small. Third, fiscal rules enhance the positive effects of discretionary fiscal policy. However, these expansionary effects on the multipliers are modest compared to earlier studies.

We derive a seminonparametric utility function containing the constant relative risk aversion (CRRA) function as a special case, and we estimate the associated Euler equations with U.S. consumption data. There is strong evidence that the CRRA function is misspecified. The correctly specified function includes lagged effects of durable goods and perhaps nondurable goods, is bounded as required by Arrow's Utility Boundedness Theorem, and has a positive rate of time preference. Constraining sample periods and separability structure to be consistent with the generalized axiom of revealed preference affects estimation results substantially. Using Divisia aggregates instead of the NIPA aggregates also affects results.

In this paper, we investigate real-time behavior of constant-gain stochastic gradient (SG) learning, using the Phelps model of monetary policy as a testing ground. We find that whereas the self-confirming equilibrium is stable under the mean dynamics in a very large region, real-time learning diverges for all but the very smallest gain values. We employ a stochastic Lyapunov function approach to demonstrate that the SG mean dynamics is easily destabilized by the noise associated with real-time learning, because its Jacobian contains stable but very small eigenvalues. We also express caution on usage of perpetual learning algorithms with such small eigenvalues, as the real-time dynamics might diverge from the equilibrium that is stable under the mean dynamics.

This paper considers a model of linear capital taxation for an economy where capital and labor income are subject to idiosyncratic uninsurable risk. To keep the model tractable, we assume that investment decisions are made before uncertainty is realized, so that the realization of the capital and labor income shocks only affects current consumption. In this setting, we are able to jointly analyze capital and labor income risk and derive analytical results regarding the optimal taxation of capital. We find that the optimal capital tax is positive in the long run if there is only capital income risk. The reason for this is that the capital tax provides insurance against capital income risk. Furthermore, for high levels of risk, increasing the capital tax may actually induce capital accumulation. On the other hand, if there is only labor income risk, the optimal capital tax is zero. The sign of the optimal tax can only be negative if the two types of risk are negatively correlated and labor income risk is large enough.

Under adaptive learning, recursive algorithms are proposed to represent how agents update their beliefs over time. For applied purposes, these algorithms require initial estimates of agents perceived law of motion. Obtaining appropriate initial estimates can become prohibitive within the usual data availability restrictions of macroeconomics. To circumvent this issue, we propose a new smoothing-based initialization routine that optimizes the use of a training sample of data to obtain initials consistent with the statistical properties of the learning algorithm. Our method is generically formulated to cover different specifications of the learning mechanism, such as the least-squares and the stochastic gradient algorithms. Using simulations, we show that our method is able to speed up the convergence of initial estimates in exchange for a higher computational cost.

This paper investigates the quantitative importance of different savings motives on the distributions of wealth and consumption and aggregate capital accumulation by solving an overlapping generations model with intragenerational heterogeneity. Agents differ in age, ability, earnings shocks, and inherited bequests. In the baseline economy, there are uninsurable idiosyncratic risks associated with uncertain lifetime and earnings shocks. The model is calibrated to the U.S. economy and solved numerically. Then the allocations of the baseline economy are compared with those of an economy with complete annuity markets, one without earnings uncertainty, and one without altruism.

Over the past few decades, both the relative price of housing structures and housing services consumption relative to nondurables increased significantly in the United States. This paper explores demand-side factors such as an increase in idiosyncratic earnings risks and changes in housing institutions as potential explanations for the phenomenon. We build a general equilibrium incomplete markets model of housing and compare two steady states that correspond to the 1967 and 2000 U.S. economies. Our model can generate the simultaneous increase in the relative price of houses and housing services consumption relative to nondurables. We find that the increased earnings risks are crucial in replicating this pattern.

In models with a representative infinitely lived household, tax smoothing implies that the steady state of government debt should follow a random walk. This is unlikely to be the case in overlapping generations (OLG) economies, where the equilibrium interest rate may differ from the policy maker's rate of time preference. It may therefore be optimal to reduce debt today to reduce distortionary taxation in the future. In addition, the level of the capital stock in these economies is likely to be suboptimally low, and reducing government debt will crowd in additional capital. Using a version of the Blanchard-Yaari model of perpetual youth, with both public and private capital, we show that it is optimal in steady state for the government to hold assets. However, we also show how and why this level of government assets can fall short of both the level of debt that achieves the optimal capital stock and the level that eliminates income taxes. Finally, we compute the optimal adjustment path to this steady state.

We explore real-time adaptive nonlinear learning dynamics in stochastic macroeconomic systems. Rather than linearizing nonlinear Euler equations where expectations play a role around a steady state, we instead approximate the nonlinear expected values using the method of parameterized expectations. Further, we assume that these approximated expectations are updated in real time as new data become available. We argue that this method of real-time parameterized expectations learning provides a plausible alternative to real-time adaptive learning dynamics under linearized versions of the same nonlinear system, and we provide a comparison of the two approaches.

We characterize the necessary and sufficient conditions for optimality in discrete-time, infinite-horizon optimization problems with a state space of finite or infinite dimension. It is well known that the challenging task in this problem is to prove the necessity of the transversality condition. To do this, we follow a duality approach in an abstract linear space. Our proof resembles that of Kamihigashi (2003), but does not explicitly use results from real analysis. As an application, we formalize Sims's argument that the no-Ponzi constraint on the government budget follows from the necessity of the tranversality condition for optimal consumption.

The credibility criterion commonly used in the strategic macroeconomic policy literature, subgame perfection or its variants, ignores a critical problem concerning intertemporal consistency of policy announcements. To capture this additional credibility constraint, this note applies two distinct notions of Renegotiation-Proof, originally proposed in the context of two-person repeated games. Macroeconomic policy games, where the benevolent government interacts with atomistic private agents, offers a new testing ground for these criteria to be evaluated. This note discusses the relative strengths and weaknesses of these criteria.