The rate of innovation in Information Technology (IT) has slowed down over time. The slowdown is evident both in the data on quality-adjusted prices of computers, and performance of microprocessors used in computers. The model in this paper shows that an IT–labor elasticity of substitution that is greater than 1 can explain the slowdown. With an elasticity of substitution greater than 1, however, slowing innovation can result in sustained labor productivity and output growth. Sustained growth is possible because an IT–labor elasticity of substitution greater than 1 results in a continuously increasing share of IT in production costs, which counteracts the effect of slowing innovation on labor productivity and output growth. In this environment of slowing innovation, increasing IT share and sustained growth, employment can increase or decrease, depending on the values of the IT–labor elasticity of substitution and the price elasticity of demand for IT-enabled consumption goods.

This paper argues that not only actual lockdowns can affect economies but also noisy information about them. We construct a New Keynesian model with imperfect information about how long the lockdown would last. On the one hand, a false signal about the lockdown lowers consumption, investment, employment, and output, and this effect can be quantitatively sizable. On the other hand, a true information about a lockdown being introduced can also be misinterpreted and hence cause an impact on agents’ decisions being quantitatively different from the one desired by the authorities. To the extent that the latter have less noisy information about future lockdowns than the private sector, they can reduce these undesired fluctuations by precisely communicating the lockdown policy. Importantly, under some circumstances only radical improvements in information precision are successful.

This paper investigates the impact of the introduction of inflation-linked bonds, which incur transaction costs when traded, on the monetary economy with sunspots. This paper shows that there always exists a certain range of positive transaction costs, where both monetary and bond markets are active. This implies that on top of governments, profit-seeking financial entrepreneurs also have the incentive to issue these bonds. This paper also displays how financial innovation on the indexed bond can be Kaldor improving, even if not necessarily Pareto improving. This finding indicates that together with lump-sum tax policies, the government can attain consensus among consumers on bond issuance.

This article quantifies the aggregate effects of firing costs in a model of firm dynamics where firm-level productivity is determined by innovation. In the model, the productivity distribution is endogenous, and thus, potentially affected by policy changes, allowing the model to capture both the static (allocative efficiency) and dynamic effects (changes in the distribution of firms’ productivity) of firing costs. The model is calibrated to match key features of firms’ hiring and firing behavior using firm-level data from Spanish nonfinancial firms. I show that firing costs equivalent to 2.5 monthly wages produce a 4% loss in aggregate productivity relative to the frictionless economy. The aggregate productivity losses rise to more than 10% when firing costs are equivalent to 1 year’s wage. I show that a model with a standard AR(1) productivity process can only generate between 45 and 50% of these losses. Overall, the results suggest that ignoring the effects of frictions on the dynamics of firms’ productivity can substantially underestimate their effects.

This paper addresses an employer’s decision to invest in firm-specific training for temporary workers within a search-matching framework with two-tier employment contracts. Based on the fact that opportunities to receive firm-provided training are significantly limited in temporary jobs, we examine whether policies aimed at inducing employers to provide training for temporary workers improve labor market performance. Our quantitative analysis produces the following results: first, reducing the cost of training temporary workers, which aims to directly increase their participation in firm-provided training, improves social efficiency but increases the unemployment rate, and decreases the share of permanent workers. Second, relaxing firing regulations on permanent jobs decreases the unemployment rate and increases the proportion of temporary workers who receive training and social welfare. Thus, a spillover effect of reforming employment protection legislation associated with permanent jobs is observed on training provision in temporary jobs.

We document that the employment effects of financial aid to US states during the Great Recession were strongly unevenly distributed across sectors, the construction sector being the main beneficiary. State fiscal relief not only preserved a substantial number of jobs but it also fostered employment most strongly in the sectors hit hardest by the recession. Exploiting across-state differences, we conclude that the sectoral employment effects of state fiscal relief reflect the typical spending patterns of state and local governments, who usually spend large shares of their discretionary expenditures on construction.

We measure how taking into account air quality affects relative welfare levels and welfare convergence across countries. We use the equivalent variation framework by Jones and Klenow [(2016) American Economic Review 106(9), 2426–2457.] which takes into account consumption, life expectancy, inequality, and leisure and extend it with respect to environmental quality in form of air pollution. Our results show that omitting environmental aspects from welfare accounting might lead to both a substantial over- or understatement of actual relative welfare and welfare developments for different (groups of) countries.

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.

I explore the welfare implications of currency union (CU) membership in a model that generates a trade-off between alternative monetary arrangements. While national currencies support country-specific monetary policies, a CU eliminates some barriers to trade and transitory cross-border price misalignments caused by nominal rigidities. I quantify the welfare gap between these two arrangements and show that it depends crucially on the correlation of shocks across the countries involved. I estimate the model with data from 11 Eurozone members and I seek the minimum trade gains needed to make a single currency worthwhile for them. I find that modest trade gains are likely to be sufficient, given the good business-cycle affiliation of these economies.

The existing output gap measures for the US economy rely on aggregate data and assume a constant output gap over sectors (see Coibion et al. [(2018) Brookings Papers on Economic Activity, 333–441] and Owyang et al. [(2018) Federal Reserve Bank of St. Louis Review, 297–316]); however, each sector has its cycle, which does not necessarily match the business cycle (Burns and Mitchell [(1946) National Bureau of Economic Research]). By modeling sectoral cycles based on their investment cycles with a nonparametric method, I estimate output gaps of 20 US sectors over 1948–2020. The weighted mean output gap indicates a persistent spare capacity in the last business cycle, pointing to insufficient stabilization policies behind secular stagnation. Phillips curve estimations with the weighted quartiles of sectoral output gaps show that the output gap of bottleneck sectors (weighted Q3) is correlated strongly with inflation over 1950–2020. Policymakers can track bottleneck sectors to mitigate inflationary pressures while supporting the sectors with negative output gaps to stabilize the output at its potential. My findings show that it is possible to produce more output by sector-level demand supporting policies without generating inflation.

This paper derives a new set of results that provide corrective measures of overall technical inefficiency that either have been ignored or wrongly assumed in the literature. Using directional distance functions, we argue that overall technical inefficiency is not only a function of input and output technical inefficiencies as previous studies claim but also of the interaction between them. The derivation of the interactive effects between input and output technical inefficiencies (IEIOs) solves the arbitrary decomposition of overall technical inefficiency into input and output components. We also show that the IEIO depends on the choice of the directional vector and whether quantities and prices are taken into consideration. Using exogenous and endogenous directional vectors, we prove these results theoretically and empirically using the US commercial banking data set. Using Bayesian estimation with the monotonicity conditions imposed at each observation, we estimate input and output technical inefficiencies separately using directional input and output distance functions with the three commonly used directional vectors; the unit value, the observed input−output, and the optimal directional vectors. The overall technical inefficiency is estimated using systems of equations to incorporate the interactive effect equation and to address the endogeneity of inputs and outputs. Consistent with the theoretical results, we find significant evidence of the IEIO which has a negative effect on the overall technical inefficiency. This result is robust to alternative directional vectors and model specifications, suggesting that the adjustability of both inputs and outputs is required for the improvement of the efficiency of the US commercial banks.

This paper revisits the canonical assumption of nonconvex capital adjustment costs in lumpy investment models as in Khan and Thomas [(2008) Econometrica 76(2), 395–436], which are assumed to follow a uniform distribution from zero to an upper bound, without distinguishing between the mean and the variance of the distribution. Unlike the usual claim that the upper bound stands for the size (represented by the mean) of a nonconvex cost, I show that in order to generate an empirically consistent interest elasticity of aggregate investment, both a sizable mean and a sizable variance are necessary. The mean governs the importance of the extensive margin in aggregate investment dynamics, while the variance governs how sensitive the extensive margin is to changes in the real interest rate. As a result, both the mean and the variance are quantitatively important for aggregate investment dynamics.