This study develops a new dynamic general equilibrium model to explore the role of people’s love of novelty as a cultural preference in innovation and innovation-based growth. The model considers (a) an infinitely lived representative consumer who has standard love-of-variety preferences for differentiated products and additional love-of-novelty preferences for new products and (b) technological progress driven by two costly and time-consuming innovation activities, new product development and existing product development. We demonstrate that consumers’ love of novelty is a source of innovation-based growth, wherein economies with a moderate love of novelty can achieve innovation and long-run growth through endogenous cycles between periods in which new product development is active and those in which existing product development is active. However, if love of novelty preference is too weak or too strong, the economy is caught in an underdevelopment trap with less innovation and no long-run growth. We also provide some suggestive empirical evidence that supports our theoretical predictions.

Many economies have recently adopted the defined-contribution retirement financing system, but one disadvantage of this system is that retirees have to bear longevity risk. As a result, several economies have also introduced the public annuity plans. We analyze the similarities and differences between voluntary public annuity with ceiling (VPAc) plan and mandatory public annuity with flexibility (MPAf) plan that are empirically observed. Introducing either plan reduces the severity of adverse selection in public annuities, but further distorts the private annuity market. These two plans have systematically different effects on retirees’ utility levels: the good health group is adversely affected and the average health group benefits. On the other hand, the poor health group benefits from the VPAc plan but may be adversely affected under the MPAf plan.

This paper proposes that an International Monetary Fund (IMF) policy shift was the reason behind major changes in sovereign debt negotiation outcomes observed in 1989. The new policy, in marked departure from past policy, allowed the IMF to lend to nations in default. The paper highlights the stark improvements in debt forgiveness and post-negotiation debt servicing ability coincident with the IMF policy shift. A theoretical framework is proposed in which the IMF policy shift causes the observed changes in negotiation outcomes. The model highlights the policy’s potential to improve a country’s outside option during negotiations of defaulted debt. In the model, this improvement leads to increased debt forgiveness which in turn leads to less post-negotiation debt servicing difficulties. The model is then used to address an important question regarding the nature of post-negotiation default risk. The case is made that countries face persistent, rather than temporary, default risk after such negotiations. To avert such risk, they moderate their borrowing.

This paper compares the impact of setting the money growth rate versus pegging the interest rate on aggregate real variables and their distributions. In either case, the monetary policy, in isolation, requires the price level to jump to ensure intertemporal solvency but has no real dynamic effects. The choice of monetary instrument has consequences for wealth and income inequality, doing so in potentially conflicting ways. Following real shocks, the accompanying monetary policy will influence the ensuing transition. For real variables, this operates entirely through its impact on the speed of convergence and is negligible. For financial variables, the impact also depends upon the initial jump in the price level. These effects vary more substantially between policies and have more significant distributional consequences. Overall, the impact on inequality is dominated by the real shocks themselves, rather than the accompanying monetary policy. Finally, we compare these two policies to inflation targeting, which is shown to be the least favorable for reducing wealth inequality, but the most favorable for reducing income inequality.

Stock market bubbles arise as a joint monetary and financial phenomenon. We assess the potential of monetary policy in mitigating the onset of bubbles by means of a Markov-switching Bayesian Vector Autoregression model estimated on US 1960–2019 data. Bubbles are detected and dated from the regime-specific interplay among asset prices, fundamental values, and monetary policy shocks. We rationalize the empirical evidence with an Overlapping Generations model, able to generate a bubbly scenario with shifts in monetary policy, and where agents form beliefs over transition dynamics. By matching the VAR impulse responses, we find that procyclicality and financial instability align with high equity premia and the presence of asset price bubbles. Monetary policy tightening, by increasing real rates, is ineffective in deflating bubble episodes.

We examine a theoretical model of liquidity with three assets—money, government bonds, and equity—that are used for transaction purposes. Money and bonds complement each other in the payment system. The liquidity of equity is derived as an equilibrium outcome. Liquidity cycles arise from the loss of confidence of the traders in the liquidity of the system. Both open market operations and credit easing play a beneficial role for different purposes.

This paper investigates the relationship between credits and sector-level output dynamics in a sample of 41 advanced and developing countries. The existing literature shows that household credits are associated with boom-bust cycles in aggregate output, whereas business loans do not cause such output dynamics. The present paper expands these findings in terms of advanced versus developing countries and manufacturing versus services sectors. The new findings indicate that the resulting boom-bust cycles in the aggregate output in response to household credits are generally observed in the sample of developing countries, with no similar dynamics in the advanced countries. Another significant conclusion is that the boom-bust cycles are generated mostly in the services sector. No equivalent boom-bust dynamics are observed in the manufacturing sector, but the negative medium-run effects of household credits are larger in this sector. These findings indicate that credit mechanisms and consequences can significantly vary across countries and sectors.

This paper studies the role of stochastic volatility in a setting where housing serves as an important propagation mechanism. After showing time-varying volatility in US house prices, we estimate a dynamic stochastic general equilibrium model with housing, financial frictions, and stochastic volatility using a nonlinear approximation and Bayesian econometric techniques. Incorporating stochastic volatility into the model greatly improves model fit and accounts for approximately half of the increased volatility in house prices observed during the Great Recession. Increased stochastic volatility escalates uncertainty which has significant effects on macroeconomic variables. While uncertainty in most sectors has negative effects on the economy, uncertainty on collateral constraints has the largest role. Unlike other uncertainty shocks, the housing demand uncertainty creates positive spillovers in the economy. Credit conditions, adjustment costs of capital and housing, and monetary policy are important transmission mechanisms for the stochastic volatility shocks.

In this paper, we empirically explore the endogeneity of uncertainty and the interaction between different types of uncertainty and monetary policy using a shock-restricted vector-autoregression model. We find that a contractionary monetary policy shock reduces financial uncertainty, opposite to the findings in the previous literature, while at the same time it also heightens real uncertainty. This discrepancy arises because the model allows endogenous shifts in uncertainty. We also show that endogenous responses of uncertainty amplify the effects of monetary policy on real activity.

This study develops a Malthusian model for the evolution of human society from hunting-gathering to agriculture and from agriculture to industrial production. Human society evolves across these stages as the population grows. However, under endogenous population growth, the population may stop growing at any stage. If it fails to reach the first threshold, the population remains as hunter-gatherers. If it reaches the first threshold, an agricultural society emerges. Then, if the population fails to reach the industrial threshold, it remains in an agricultural Malthusian trap without experiencing industrialization. Interestingly, high agricultural productivity triggers not only the Neolithic Revolution but also the subsequent industrialization. Using cross-country data to test this result, we employ an index of prehistoric biogeographic conditions that affect agricultural productivity as an instrument for the timing of transitions to agriculture and find that an earlier transition to agriculture has a positive effect on industrialization in the modern era.

Optimal monetary policy, under flexible and sticky prices, and sticky nominal wages are studied in the canonical matching model of the labor market with a working capital channel. A money demand by firms is motivated by the fact that a significant amount of M1 is held by firms. As a result of the working capital, the Ramsey-optimal monetary policy calls for inflation when employment is above the socially efficient level and for deflation when it is below that level. This result holds under flexible wages as well as nominal wage rigidities. In other words, to improve labor market efficiency, deflation is necessary to “grease the wheels of the labor market.” Although there is no relationship between optimal monetary policy and the market tightness under flexible prices, a long-run and mainly negative relationship between the optimal inflation rate and the equilibrium tightness emerges under sticky prices.

This paper develops an efficient Stein-like shrinkage estimator for estimating slope parameters under structural breaks in seemingly unrelated regression models, which is then used for forecasting. The proposed method is a weighted average of two estimators: a restricted estimator that estimates the parameters under the restriction of no break in the coefficients, and an unrestricted estimator that considers break points and estimates the parameters using the observations within each regime. It is established that the asymptotic risk of the Stein-like shrinkage estimator is smaller than that of the unrestricted estimator, which is the method typically used to estimate the slope coefficients under structural breaks. Furthermore, this paper proposes an averaging minimal mean squared error estimator in which the averaging weight is derived by minimizing its asymptotic risk. Insights from the theoretical analysis are demonstrated in Monte Carlo simulations and through an empirical example of forecasting output growth of G7 countries.

In many countries, the structure of wages and the labor law legislation are completely different for public and private sector employees. In this paper, we develop a general equilibrium overlapping generations model to study the effect of such differences on household savings and labor supply. To conduct our analysis, first we use microdata from two Brazilian household surveys to document that civil servants save and work significantly less than their counterparts in the private sector. Second, we use matched employer–employee microdata from Brazil (RAIS) to document differences between the two sectors in terms of wage and unemployment risk. Then, we calibrate the model to be consistent with micro and macro evidence for Brazil. Our counterfactual exercises show that differences in wages characteristics and labor law legislation account for nearly 70% of the gap in savings between civil servants and private sector workers, and 57% of the gap in labor supply. In addition, we find that eliminating those differences can produce sizable increase on aggregate savings, employment, and welfare.

This paper incorporates the variable elasticity of substitution preferences in the variety expansion model developed by Grossman and Helpman [(1991) Innovation and Growth in the Global Economy, MIT Press]. There exists a balanced growth path when the elasticity of substitution is constant with knowledge spillover. When the elasticity of substitution is variable and the knowledge spillover is sufficiently small, a unique and stable steady state exists. When the knowledge spillover is sufficiently large, the steady state is unique and unstable. When the size of the knowledge externality is moderate, multiple equilibria exist.

I develop and study a factor-augmented quasi-vector autoregressive (FAQVAR) model for economic policy analysis in tumultuous times. An observation-driven framework that exploits the information from the score of the model allows a maximum likelihood estimation. This multivariate FAQVAR model, which assumes a Student t error distribution, is robust to atypical observations such as the global financial crisis and the recent pandemic. The model outperforms the FAVAR moving average model because of the assumed heavy tails that capture the COVID-19 atypical data and other turbulent episodes. An empirical application to the U.S. economy assessing its monetary policy reveals that estimates and impulse responses are stable when considering the sample before and during COVID-19.

We study an OLG model with child policies and a PAYG pension with endogenous retirement and fertility. The result of the planned economy is compared to the decentralized competitive equilibrium deriving optimal policies. We show that in the presence of a PAYG pension system, the optimal policy mix includes an education subsidy and a subsidy for the supply of labor in old age. Fertility should be taxed or incentivized depending on whether there is full or partial retirement, and on the parameters. We focus on the parameter reflecting the deterioration of human capital and show that a child tax may be required.

The US Social Security program was created in part as an explicit response to the Great Depression. We evaluate the performance of Social Security as a protective safety net against a rare episode of sudden and significant loss of private wealth such as the Great Depression. We construct a model in which a rare event causes a shock to wealth at an unknown time. How well does Social Security function as a safety net against such risk? The answer depends critically on whether households optimize in the face of this risk. If the household has full information on the distribution of rare event risk and solves a dynamic stochastic problem to hedge this risk, then Social Security is unnecessary along this dimension. Alternatively, if the household does not account for rare event risk in its financial planning, then Social Security can provide very large welfare gains as a safety net.

A general wisdom, since at least the work of Schmitt-Grohé and Uribe [(1997) Journal of Political Economy 105, 976–1000.], holds that a government that relies on adjusting factor income tax rates to achieve budget objective may induce aggregate instability driven by self-fulfilling expectations. This paper shows that this conventional wisdom may be overturned if the rate of adjustment of the capital income tax rate is bigger than that of the labor income tax rate. How much bigger depends on country specifics and particularly on the levels of the capital and labor income tax rates. Thus, adjustments in capital and labor income tax rates, if properly designed and implemented, can help achieve the budget objective while at the same time preempting extrinsic volatility.

This empirical paper deals with the impacts of sentiment about the future, short-run risk, and long-run risk in a dynamic economic model of optimal consumption decisions with Schroder and Skiadas [(1999) Journal of Economic Theory 89, 68–126.] continuous-time stochastic recursive preferences. The empirical strategy combines both a latent factor method and a democratic orthogonalization technique. The latent factor method is applied to a large database of macroeconomic indicators, and a democratic orthogonalization technique is used to separate the relative importance of sentiment about the future and long-run risk channels in shaping optimal consumption decisions. The empirical results suggest that consumers with recursive preferences are not indifferent to long-run uncertainty shocks to future consumption prospects. Endogenous consumption variations are driven by a multicomponent mechanism, where on average, the sentiment component accounts for 15.33%, the short-run risk accounts for 16.89%, and the long-run risk pertains to 34.51%.

We develop a simple two-sector neoclassical growth model in which the upstream sector produces intermediate goods, and the downstream sector produces final goods with outputs from the upstream. While the downstream sector features perfect competition, firms in the upstream sector engage in Cournot competition and charge a markup. We show that the deregulation and the introduction of competition in the upstream goods sector not only increases the productivity in the sector but also has a substantial spillover effect on the productivity of the downstream sector and factor prices. We calibrate the model to the Chinese economy and use the calibrated model to quantitatively evaluate the extent to which the deregulation in the upstream market in China from 1998 to 2006 can account for the rapid economic growth and the high and rising returns to capital in China over the same period. Our quantitative experiments show that the deregulation in the upstream sector can account for a significant share of economic growth in China during the study period. In addition, our model delivers implications that are consistent with several other relevant observations in China during the same period.