Rigorous methods have recently been developed for statistical inference of Malmquist productivity indices (MPIs) in the context of nonparametric frontier estimation, including the new central limit theorems, estimation of the bias, standard errors and the corresponding confidence intervals. The goal of this study is to briefly overview these methods and consider a few possible improvements of their implementation in relatively small samples. Our Monte-Carlo simulations confirmed that the method from Simar et al. (2023) is useful for the simple mean and aggregate MPI in relatively small sample sizes (e.g., up to around 50) and especially for large dimensions. Interestingly, we also find that the “data sharpening” method from Nguyen et al. (2022), which helps in improving the approximation in the context of efficiency is not needed in the context of estimation of productivity indices. Finally, we provide an empirical illustration of the differences across the existing methods.

This study investigates the contribution of financial frictions in term premiums on long-term bonds within a production economy. We consider a New Keynesian model, featuring an agency problem between financial intermediaries and their private creditors and generalized recursive preferences. The model predicts that financial frictions that amplify the impact of structural shocks on key macroeconomic variables increase term premiums under our baseline calibration. Furthermore, financial frictions produce a larger term premium when monetary policy is geared toward output over inflation stability. The novel mechanism that financial frictions increase term premiums are associated with the bank balance sheet channel of monetary policy.

This paper investigates the bidirectional relation between the Brazilian Central Bank communication and the yield curve. Using latent factors, observable macroeconomic variables, and observable variables representing Central Bank communication, we estimate a model that summarizes the yield curve. We find evidence of the effects of Brazilian Central Bank communication on the movements of the yield curve and the impact of the yield curve components in Brazilian Central Bank communication. In particular, Central Bank communication can shape yield curve curvature and slope. Additionally, we find a strong relation between Central Bank communication and the curvature of the yield curve. These results show that Central Bank communication impacts market players, making it a valuable instrument for monetary policy.

This paper examines an endogenous growth model that allows us to consider the dynamics and sustainability of debt, pollution, and growth. Debt evolves according to the financing adaptation and mitigation efforts and to the damages caused by pollution. Three types of features are important for our analysis: the technology through the negative effect of pollution on TFP; the fiscal policy; the initial level of pollution and debt with respect to capital. Indeed, if the initial level of pollution is too high, the economy is relegated to an endogenous tipping zone where pollution perpetually increases relatively to capital. If the effect of pollution on TFP is too strong, the economy cannot converge to a stable and sustainable long-run balanced growth path. If the income tax rates are high enough, we can converge to a stable balanced growth path with low pollution and high debt relative to capital. This sustainable equilibrium can even be characterized by higher growth and welfare. This last result underlines the role that tax policy can play in reconciling debt and environmental sustainability.

We construct a Divisia money measure for U.K. households and private non-financial corporations and a corresponding dual user cost index employing a consistent methodology from 1977 up to the present. Our joint construction of both the Divisia quantity index and the Divisia price dual facilitates an investigation of structural vector autoregresssion models (SVARs) over a long sample period of the type of non-recursive identifications explored by Belongia and Ireland (2016, 2018), as well as the block triangular specification advanced by Keating et al. (2019). An examination of the U.K. economy reveals that structures that consider a short-term interest rate to be the monetary policy indicator generate unremitting price puzzles. In contrast, we find sensible economic responses in various specifications that treat our Divisia measure as the indicator variable.

A growing body of literature proposes a climate-oriented monetary and financial policy for Central Banks (CBs). However, other literature defends a market-neutral monetary policy to keep CB independence and avoid addressing other than conventional objectives. However, if the CBs’ market-neutral policy is only targeting inflation rates and employment, it could amplify the macro impacts of negative economic externalities, while also neglecting positive externalities in the long-run. Even if climate-related policy goals appear advisable, the actions of CBs reveal significant delayed impacts on macro and climate-risk variables. We propose a non-linear dynamic macro model of finite horizon with multiple targets, including macro imbalances and climate risks arising from a trend in carbon emissions. This non-stationary emission dynamic has feedback effects on stationary and non-stationary macro variables and the multiple (possibly conflicting) objectives of the CBs. In this context, we first explore to what extent CBs can impact emission trends with and without delays. Second, given the mix of stationary and non-stationary dynamic variables, we explore the responses to policy and economic and financial shocks using a mixed Vector Error Correction Model (VECM) with stationary and non-stationary variables. Third, in the face of multiple objectives—and macroeconomic concerns that CBs face—we are motivated by Kaya and Maurer (2023) to construct a Pareto front that introduces weights for the multiple objectives and permits target prioritization.

Risk was incorporated into monetary aggregation over thirty-five years ago, using a stochastic version of the workhorse money-in-the-utility-function model. Nevertheless, the mathematical foundations of this stochastic model remain shaky. To firm the foundations, this paper employs richer probability concepts than Borel-measurability, enabling me to prove the existence of a well-behaved solution and to derive stochastic Euler equations. This measurability approach is less common in economics, possibly because the derivation of stochastic Euler equations is new. Importantly, the problem’s economics are not restricted by the approach. The results provide firm footing for the growing monetary aggregation under risk literature, which integrates monetary and finance theory. As crypto-currencies and stable coins garner attention, solidifying the foundations of risky money becomes more critical. The method also supports deriving stochastic Euler equations for any dynamic economics problem that features contemporaneous uncertainty about prices, including asset pricing models like capital asset pricing models and stochastic consumer choice models.

This paper examines the impact of financially constrained intermediate inputs on within-industry total factor productivity loss. Utilizing exogenous tax reforms in China as a natural experiment, our difference-in-difference analysis reveals that reduced tax burdens lead to increased firm-level intermediate inputs, particularly among financially constrained firms. We incorporate financially constrained intermediate inputs into a partial equilibrium model of firm dynamics. Our calibration suggests that financially constrained intermediate inputs play a quantitatively more important role in accounting for misallocation than financially constrained capital. The presence of financially constrained intermediate inputs introduces a downward bias in the measurement of value-added productivity, especially for firms in the top decile of gross-output productivity. As a result, the average “efficient” levels of capital and labor for the top decile firms in the standard Hsieh and Klenow (2009) exercise are lower than what is truly efficient.

How do geopolitical risk shocks impact monetary policy? Based on a panel of 18 economies, we develop and estimate an augmented panel Taylor rule via constant and time-varying local projection regression models. First, the panel evidence suggests that the interest rate decreases in the short run and increases in the medium run in the event of a geopolitical risk shock. Second, the results are confirmed in the time-varying model, where the policy reaction is accommodating in the short run (1 to 2 months) to limit the negative effects on consumer sentiment. In the medium term (12 to 15 months), the central bank is more committed to combating inflation pressures.

Building on Lucas (1988) and Boucekkine et al. (2013), we develop a model in which the impact of population dynamics on per capita GDP and human capital depends on the balance of intertemporal altruism effects toward future generations and class-size effects on an individual’s education investment. We show that there is a critical level of the class-size effects that determines whether a decline in population growth will lead to a decrease or an increase in a country’s long-run growth rate of real per capita income. We take the model to OECD data, using a semi-parametric technique. This allows us to classify countries into groups based on their long-term growth trajectories, revealing patterns not captured by previous studies on the topic.

This paper presents an algorithm for simulating multiple equilibria in otherwise-linear dynamic models with occasionally-binding constraints. Our algorithm extends the guess-and-verify approach of Guerrieri and Iacoviello (2015) to detect and simulate multiple perfect foresight equilibria, and allows arbitrary “news shocks” up to a finite horizon. When there are multiple equilibria, we show how to compute expected paths using a “prior probabilities” approach and we provide an approach for running stochastic simulations with switching between equilibria on the simulated path. A policy application studies a New Keynesian model with a zero lower bound on nominal interest rates and multiple equilibria, including a “bad” solution based on self-fulfilling pessimistic expectations. A price-level targeting rule does not always eliminate the bad solution, but it shrinks the indeterminacy region substantially and improves stabilization and welfare relative to more conventional interest rate rules or forward guidance.

At the firm level, productivity is constantly evolving because of the introduction of new technology and innovations. Some of these productivity gains diffuse uniformly across firms, while others only spread out in the industry with time. The unequal evolution of productivity impacts the structure of the industry, the more the greater the degree of competition. We analyze the relationship between the distribution of firms’ productivity advantages and the distribution of market shares and show that this relationship is more intense with more competition. We briefly comment on two applications: we show that because productivity gains, market concentration and inflation can be negatively related, and we give an alternative interpretation to the case for a recent rise of US markups attributed to increased market power.

I use a new publicly available industry-year panel dataset capturing within-industry productivity dispersion to examine the relationship between various measures of industry-level leverage, a common measure of financial constraints, and industry-level productivity dispersion, a common measure of misallocation. Increases in short-term leverage are associated with increases in TFPR dispersion. Likewise, increased short-term leverage is associated with a persistent increase in labor productivity dispersion. Higher long-term leverage is generally associated with higher dispersion in TFPR. However, there is little correlation between long-term leverage and labor productivity dispersion. On the asset side of the balance sheet, the accumulation of inventories is associated with lower dispersion. I interpret these results in a model featuring sources of finance with different time horizons and nonuniform financial constraints across inputs.

Efficiency is a crucial factor in productivity growth and the optimal allocation of resources in the economy; therefore, measuring inefficiency is particularly important. This paper provides a comprehensive review of the latest developments in distance functions and the measurement of inefficiency within the stochastic frontier framework. Recent advances in several related areas are reviewed and evaluated, including various approaches to measuring inefficiency using distance functions, advancements in modeling inefficiency within the stochastic frontier framework, and the most common estimation techniques. A practical guide is provided on when these methods can be applied and how to implement them. The radial, hyperbolic, and directional measures of inefficiency are discussed and assessed. The development of modeling inefficiency concerning its temporal behavior, classification, and determinants is also examined. To ensure the use of appropriate estimation techniques, recent advancements in the most common estimation techniques are reviewed. This paper also addresses the importance of maintaining the theoretical regularity applied by neoclassical microeconomic theory when it is violated, as well as the econometric regularity when variables are non-stationary. Without regularity, inefficiency results can be extremely misleading. The paper discusses significant challenges related to estimation issues that must be managed in future applications. These challenges include the inaccurate choice of functional form, ignoring the possibility of heterogeneity and heteroskedasticity, and suffering from the endogeneity problem. The paper also examines various approaches to addressing these issues, as well as potentially productive areas for future research.

Our spatial general equilibrium model evaluates the impact of stamp duty reforms on social welfare through two channels: the direct positive impact on housing market outcomes and the indirect boost to national productivity due to better labor allocation. Analyzing detailed spatial data from Australia, we find that reducing stamp duties generates welfare gains of 3.57%, with the productivity channel accounting for 95% of these gains. This highlights the significant benefits of stamp duty reforms beyond the housing market.

This paper adds to the literature on global inflation synchronization by distinguishing the traded and non-traded content of the consumption basket. Using a novel database of monthly CPI series of 40 countries from 2000, a dynamic factor model with stochastic volatility decomposes inflation into global, income-group, and idiosyncratic components. While synchronization has historically been prominent in tradable goods inflation, findings also reveal an increasing synchronization in non-tradable inflation. Second, I use a time-varying parameter vector autoregressive model to investigate the potential spillover effect. The results provide evidence of spillover from tradable to non-tradable inflation, while the reverse is mainly muted over the sample. Finally, results from local projections indicate that a tightening of US monetary policy causes a significant decline in global headline inflation, which is primarily driven by the heightened sensitivity of tradable goods.

The cross-sectional distribution of government debt is often approximated by a lognormal distribution. This note empirically demonstrates that government debt is more accurately characterized by the double Pareto-lognormal (dPLN) distribution, which features a lognormal body with two Pareto tails. The dPLN assuredly surpasses alternative parametric distributions and passes goodness-of-fit tests. With its analytical tractability, flexibility, and parsimony, coupled with a theoretical foundation, the dPLN may be appealing for different computational and empirical applications.

Technical progress is considered a key element in the fight against climate change. It may take the form of technological breakthroughs, that is, shocks that induce significant leaps in the stock of knowledge. We use an endogenous growth framework with directed technical change to analyze the climate impact of such shocks. Two production subsectors coexist: one subsector is fossil-based, using a non-renewable resource, and yields carbon emissions; the other subsector uses a clean, renewable resource. At a given date, the economy benefits from an exogenous technology shock. We fully characterize the general equilibrium and analyze how the shock modifies the economy’s trajectory. The overall effect on carbon emissions basically depends on the substitutability between the production subsectors, the initial state of the economy, and the nature and size of the shock. We notably show that green technology shocks induce higher short-term carbon emissions when the two subsectors are gross complements, but also in numerous cases when they are gross substitutes.

We assess how an economy’s wealth distribution shapes its labor market dynamics. We do so in a quantitative job-ladder model featuring directed search, incomplete markets, aggregate shocks, and endogenous on-the-job human capital accumulation. Poorer workers apply for lower-wage jobs when unemployed and under-accumulate human capital when employed to self-insure against unemployment risk. In response to an aggregate downturn, poorer workers reduce their human capital accumulation, all else equal, while richer workers increase it. The wealth distribution therefore matters for the response of aggregate human capital. In the calibrated model, we show that a negative aggregate productivity shock leads to a persistent decline in aggregate human capital, and a more dispersed wealth distribution would amplify this decline.