We provide a theory-based inquiry into the contours of China's international balance sheets after the renminbi becomes convertible under the capital account. We construct a two-country general equilibrium model with trading in equities and bonds and calibrate the model with U.S. and Chinese data. We interpret Chinese capital account liberalization as a removal of restrictions that prohibit agents trading Chinese bonds and U.S. equities. We explore how international risk-sharing can be achieved through portfolio diversification in each of these asset market configurations. We also look at how these holdings would change as China gradually rebalanced its production with a larger share of labor income, and as the productivity gap between China and the United States narrowed. We find that both U.S. and Chinese residents would have incentives to increase their holdings in each other's equities and to issue debt in each other's currency.

How should central banks optimally aggregate sectoral inflation rates in the presence of imperfect labor mobility across sectors? We study this issue in a two-sector New-Keynesian model and show that a lower degree of sectoral labor mobility, ceteris paribus, increases the optimal weight on inflation in a sector that would otherwise receive a lower weight. We analytically and numerically find that, with limited labor mobility, adjustment to asymmetric shocks cannot fully occur through the reallocation of labor, thus putting more pressure on wages, causing inefficient movements in relative prices, and creating scope for central bank’ s intervention. These findings challenge standard central banks’ practice of computing sectoral inflation weights based solely on sector size and unveil a significant role for the degree of sectoral labor mobility to play in the optimal computation. In an extended estimated model of the US economy, featuring customary frictions and shocks, the estimated inflation weights imply a decrease in welfare up to 10% relative to the case of optimal weights.

A model is constructed in which trading partners are asymmetrically informed about future trading opportunities and spatial and informational frictions limit arbitrage between markets. These frictions create inefficiency relative to a full-information equilibrium, and the extent of this inefficiency is affected by monetary policy. A Friedman rule is optimal under a wide range of circumstances, including ones where segmented markets limit the extent of monetary policy intervention.

This paper examines the long-run relationship between trade openness and government size in a two-country dynamic general equilibrium model. We analytically show that different factor intensities in the production of tradable and nontradable sectors affect the government's response to changes in trade openness. Specifically, if the production of the nontradable sector is more capital-intensive, a positive relationship between trade openness and government size will be observed. In contrast, if the production of the tradable sector is more capital-intensive, a negative correlation between trade openness and government size will arise. This theoretical prediction is robust to both utility-enhancing and productive government expenditures. The differentiated factor intensities therefore provide a potential explanation to the mixed empirical findings in the literature about the long-run relation of trade openness and government size.

It has repeatedly been shown that properly constructed monetary aggregates based on index number theory (such as Divisia money) vastly outperform traditional measures of money (i.e. simple sum money) in empirical models. However, opponents of Divisia frequently claim that Divisia is “too complex” for little gain. And indeed, at first glance it looks as if simple sum and Divisia sum exhibit similar dynamics. In this paper, we want to build deeper understanding of how and when Divisia and simple sum differ empirically using monthly US data from 1990M1 to 2007M12. In particular, we look at how they respond differently to monetary policy shocks, which seems to be the most essential aspect of those differences from the perspective of the policy maker. We use a very rich, fairly agnostic setup that allows us to identify many potential nonlinearities, building on a smoothed local projections approach with automatic selection of the relevant interaction terms. We find, that—while the direction of change is often similar—the precise dynamics differ sharply. In particular in times of economic uncertainty, when the proper assessment of monetary policy is most relevant, those existing differences are drastically augmented.

Sweden has a long and distinguished tradition in economics, beginning with Knut Wicksell and continuing with Gustav Cassel, Eli Heckscher, Erik Lindahl, Gunnar Myrdal, Bertil Ohlin, and Erik Lundberg, all of whom are now gone. Yet, for several of these men, economics was not enough: Wicksell spoke out on moral issues and served time in jail, and Myrdal was for many years a high official at the United Nations and, briefly, a cabinet minister, as was Ohlin, who made his mark at home primarily as leader of the opposition in a country governed mostly by Social Democrats, serving in parliament for 32 years. For Assar Lindbeck, however, economics has been broad enough: he has devoted a long and distinguished career to economics, and to economics alone, with unfailing enthusiasm and energy over half a century. Not that he was not wanted elsewhere: over the years, he has declined challenging job offers from an international organization and a Swedish daily newspaper, to name but two examples, as well as from universities outside Sweden. Assar has managed to harness his varied and wide-ranging talents within the many mansions of economics. He is one of the most versatile economists of his generation. Indeed, he is one of the few who, for clarity, need to divide their bibliography into categories by subject: Macroeconomics and monetary economics, Public economics, Labor economics, International economics, Economic systems and economic structures, Methodology and history of economic thought, and Swedish economy. His work on these different subjects has ranged from pure theory to applied policy-oriented and empirical studies. In addition to the numerous scientific publications listed at the end of this interview, his bibliography includes nearly 200 articles for magazines and newspapers. His ivory tower has always been equipped with a high-speed elevator. But, as he points out in the conversation to follow, all his research work, as well as his journalism, is driven by an overarching interest in bettering economic policy and organization—in other words, boosting economic and social efficiency for the purpose of lifting ordinary people's standard of life. This has been, and remains, a guiding principle—a Leitmotiv, if you prefer—from which he has never swerved. Assar Lindbeck is a towering figure in Swedish economics and in Swedish national life.

We use a labor search model with heterogenous households and firms to study the efficacy of a wage subsidy during a pandemic, relative to enhancing unemployment benefits. A large proportion of the economy is forced to shut down, and firms in that sector choose whether to lay off workers or keep them on payroll. A wage subsidy encourages firms to keep workers on payroll, which speeds up labor market recovery after the pandemic ends. However, a wage subsidy can be costlier than enhancing unemployment benefits. If the shutdown is long or profit margins are low, then a wage subsidy is preferable and vice versa. The optimal mixture of policies includes a wage subsidy that covers 90$\%$ of the first $200/week of earnings and expands unemployment benefits to cover all salary up to $275/week. Low-income workers, as well as those in less productive jobs, benefit the most from a wage subsidy.

Typically, contractionary monetary policy shocks increase the nominal and real rate of interest, which reduces both inflation and output . In contrast, the neo-Fisher effect (NFE) suggests that a transitory but persistent increase in the nominal rate of interest increases inflation in the short run. In a New Keynesian model augmented with several frictions, including the cost channel of monetary policy, real wage rigidity, habit formation in consumption, dampened expectations, and anticipated monetary policy shocks, we derive analytical conditions that give rise to (or avert) the NFE. We show that the NFE can arise due to the interplay between these frictions, and not only when the persistence of the policy shock is large, or when agents are forward-looking, as documented by the existing literature.

Over the past decade, the most salient changes in macroeconomic conditions in developed economies have included rising government debt and population aging, which are strongly correlated with each other. This paper investigates fiscal multipliers by disentangling the effects of population aging from those of government debt. Our analysis, which uses heterogeneous panel data from 24 OECD economies, shows that while fiscal policy is ineffective for economies with high-debt levels, it is effective for economies with low-debt levels. Furthermore, the estimation results reveal that fiscal policy is ineffective for aged economies, regardless of the level of government debt. However, for nonaged economies, while fiscal policy leads to negative effects on output in times of high debt, its positive effects are more pronounced in times of low debt. Our results suggest that, for the effective implementation of fiscal stimulus policies, policy-based stimulation of employment in the labor market is essential.

Expectations are among the main driving forces for economic dynamics. Therefore, managing expectations has become a primary objective for monetary policy seeking to stabilize the business cycle. In this paper, we study whether central banks can manage private-sector expectations by means of publishing one-period ahead inflation projections in a New Keynesian learning-to-forecast experiment. Subjects in the experiment observe these projections along with the historic development of the economy and subsequently submit their own one-period ahead inflation forecasts. In this context, we find that the central bank can significantly manage private-sector expectations and that this management strongly supports monetary policy in stabilizing the economy. Moreover, published central bank inflation projections drastically reduce the probability of a deflationary spiral after strong negative shocks to the economy.

An article published in 2018 by J.D. Hamilton gained significant attention due to its provocative title, “Why you should never use the Hodrick-Prescott filter.” Additionally, an alternative method for detrending, the Hamilton regression filter (HRF), was introduced. His work was frequently interpreted as a proposal to substitute the Hodrick–Prescott (HP) filter with HRF, therefore utilizing and understanding it similarly as HP detrending. This research disputes this perspective, particularly in relation to quarterly business cycle data on aggregate output. Focusing on economic fluctuations in the United States, this study generates a large amount of artificial data that follow a known pattern and include both a trend and cyclical component. The objective is to assess the effectiveness of a certain detrending approach in accurately identifying the real decomposition of the data. In addition to the standard HP smoothing parameter of $\lambda = 1600$, the study also examines values of $\lambda ^{\star }$ from earlier research that are seven to twelve times greater. Based on three unique statistical measures of the discrepancy between the estimated and real trends, it is evident that both versions of HP significantly surpass those of HRF. Additionally, HP with $\lambda ^{\star }$ consistently outperforms HP-1600.

This paper proposes a Bayesian approach to estimating a factor-augmented GDP per capita equation. We exploit the panel dimension of our data and distinguish between individual-specific and time-specific factors. On the basis of 21 technology, infrastructure, and institutional indicators from 82 countries over a 19-year period (1990 to 2008), we construct summary indicators of each of these three components in the cross-sectional dimension and an overall indicator of all 21 indicators in the time-series dimension and estimate their effects on growth and international differences in GDP per capita. For most countries, more than 50% of GDP per capita is explained by the four common factors we have introduced. Infrastructure is the greatest contributor to total factor productivity, followed by technology and institutions.

In the economics literature, there are two dominant approaches for solving models with optimal experimentation (also called active learning). The first approach is based on the value function and the second on an approximation method. In principle the value function approach is the preferred method. However, it suffers from the curse of dimensionality and is only applicable to small problems with a limited number of policy variables. The approximation method allows for a computationally larger class of models, but may produce results that deviate from the optimal solution. Our simulations indicate that when the effects of learning are limited, the differences may be small. However, when there is sufficient scope for learning, the value function solution seems more aggressive in the use of the policy variable.

We build quadratic labor adjustment costs into an otherwise standard New Keynesian model of the business cycle and show that this increases output persistence in a vein similar to that of other models of labor market frictions. Furthermore, we demonstrate the implication of quadratic labor adjustment costs for monetary policy. We show that there is a simple rule determining whether quadratic labor adjustment costs imply a trade-off between stabilizing inflation and output.

A simple asset pricing model with both endogenous stock market participation and subjective risk can explain the negative cross-country correlation between participation rates and the volatility of excess returns, along with the time-varying participation rates in the data. Belief-driven learning dynamics can explain the interplay between participation rates, subjective risk, and stock price volatility. When agents adaptively learn about the risk and return, my model generates 25% of the excess volatility observed in US stock prices, while also matching key moments. With learning about risk, excess volatility of stock prices is driven by fluctuations in the participation rate that arise because agents’ risk estimates vary with prices. I find that learning about risk is quantitatively more important than learning about returns.

This paper extends the existing theories of directed technical change by allowing the factors of production, skilled, and unskilled workers, to be employed in both the skill-intensive and unskilled-intensive sectors. Consequently, the direction of technical progress and the sectoral allocation of factors are jointly determined. The feedback between technical progress and the allocation of factors leads to new results concerning structural change and directed technical change. An increase in the endowment of a factor leads to a dynamic reallocation of factors toward the sector that uses the factor intensively. The reallocation of factors also affects the stability properties of directed technical change. When the parameter conditions necessary for strong bias are satisfied, the interior regime (nonspecialization) is at most locally stable. More importantly, if the relative endowment of skilled labor becomes too high (low), the economy necessarily specializes in the production of skilled (unskilled)-labor-intensive goods. Last, the relationship between the relative endowment of skilled labor and the steady-state relative wage rate is not necessarily monotonic.

In this article we use Bayesian classification and finite mixture models to extract information from the MSI database (maintained by the Federal Reserve Bank of St. Louis) and construct a new set of non-nested monetary aggregates (under the Divisia aggregation procedure) based on statistical similarities and multidimensional structures. We also use recent advances in the fields of applied econometrics, dynamical systems theory, and statistical physics to investigate the relationship between the new money measures and economic activity. The empirical results offer practical evidence in favor of this approach to monetary aggregation.

This paper investigates how the different food aid programs affect economic development via their effect on the parental trade-off between the number of children and the investment in each child's human capital. This is done in an OLG framework where parents decide on the number of children and the nutrition and secondary schooling of each child. Primary schooling is mandatory. Providing school meals locks countries with no children attending secondary schooling into poverty by reducing the private (nutrition) cost per child. In countries where parents find it optimal to enroll children in secondary schooling, food aid increases the marginal benefit of schooling. Consequently, school feeding programs are conducive to economic development in these countries. If food aid is in the form of a food price subsidy, we show that child nutrition and thus children's human capital increase unambiguously. Although fertility and schooling are not directly affected, a sufficiently high subsidy rate will induce parents to begin to enroll children into secondary schooling by the assumed complementarity between nutrition and schooling in the human capital production function. If the food aid program provides a fixed amount of food per child, this decreases the marginal benefit of parental nutritional investments; therefore, it leads to higher fertility and to lower total provision of nutrition per child.

In a second-best optimal growth setup with only factor taxes, it is in general optimal to fully replace capital by labor income taxation in the long run. We revisit this important issue by developing a human-capital-based endogenous growth model with frictional labor search, allowing each firm to create multiple vacancies and each worker to determine market participation. We find that the conventional efficient bargaining condition is necessary but not sufficient for achieving constrained social optimality. We then conduct tax incidence exercises in balanced growth by calibrating to the U.S. economy with a preexisting 20% flat tax on capital and labor income. Our quantitative results suggest that, due to a dominant channel via the interactions between vacancy creation and market participation, it is optimal to switch only partially from capital to labor taxation in a benchmark economy where human-capital formation depends on both physical and human-capital stocks. This main finding is robust even along the transition with time-varying factor tax rates. Moreover, our quantitative analysis under alternative setups suggests that while endogenous human capital and labor-market frictions are essential for obtaining a positive optimal capital tax, endogenous leisure, nonlinear human-capital accumulation and endogenous growth are not crucial.

This paper compares different implementations of monetary policy in a new-Keynesian setting. We can show that a shift from Ramsey optimal policy under short-term commitment (based on a negative feedback mechanism) to a Taylor rule (based on a positive feedback mechanism) corresponds to a Hopf bifurcation with opposite policy advice and a change of the dynamic properties. This bifurcation occurs because of the ad hoc assumption that interest rate is a forward-looking variable when policy targets (inflation and output gap) are forward-looking variables in the new-Keynesian theory.