Using a unique dataset that links the production and sales activities of Chinese exporting firms, we document a systematic wedge between the value of goods firms produce for export and the value of goods they sell in foreign markets. We show that this pattern reflects the presence of exporters that also operate as trade intermediaries, which we term producer intermediaries. We further document that firms with greater accumulated marketing expenditures are more likely to become producer intermediaries. Motivated by these facts, we develop a theoretical framework in which firms can lend and borrow customer capital through outsourcing relationships. In this environment, firms with high foreign customer capital can facilitate trade by channeling export demand to more productive firms with limited customer capital, even when frictions impede efficient outsourcing. Estimating the model, we find that the gains from outsourcing are substantial and that producer intermediaries account for a large share of these gains.

This paper investigates the effects of relative price shifts on aggregate labour productivity (ALP) growth in the UK. Using two extended sectoral decomposition frameworks, we isolate the contribution of relative output price changes to ALP growth and compare recent double-deflated UK data with counterfactual single-deflated data to examine the interplay between relative price contributions and productivity performance. Our analysis reveals significant relative price effects on ALP growth in manufacturing and ICT under an extended T$\ddot{o}$rnqvist decomposition but only in ICT when applying an extended Generalized Exactly Additive Decomposition (GEAD) framework. To assess whether shifts in market power explain these significant changes in relative prices, we estimate aggregate markups for manufacturing and ICT. The findings highlight substantial variations in markups from 2008 to 2019, reflected in notable fluctuations in price effects over time. These results raise important questions about the relative roles of value creation and the labour contribution in assessing the UK’s productivity performance.

Misallocation of workers and their human capital across sectors has negative implications for productivity. The literature examining this type of labor misallocation has mostly assumed a Cobb–Douglas production function, which is at odds with important macroeconomic frameworks and empirical evidence. Our paper hence suggests a new twist to revisit the question: to what extent does human capital misallocation across sectors explain why some countries are so much richer than others? Our innovation consists of incorporating a more flexible and empirically plausible CES production structure with different labor skill types into the misallocation literature. The results from this analysis indicate that human capital misallocation can explain approximately 15% of output per worker variation across countries, which is about one fourth less than under the conventional Cobb–Douglas specification (21%). This suggests that labor market efficiency may be less of a problem for aggregate productivity differences than previously thought.

COVID-19 led to the single largest year-over-year decline in Latin America’s GDP per capita in more than a century. Although the region has endured several macroeconomic shocks before, mostly related to financial dislocations, none has been so deep and synchronized, as measured by the negative co-movement of GDP rates in the major regional economies. Our analysis of the COVID-19 experience for the region and eight economies with available historical data reveals the extent of the damage. Through 2020, four economies suffered “rare disasters” (cumulative contractions by 10% or more): Argentina, Mexico, Peru, and Venezuela. In addition, Argentina, Brazil, Mexico, and Venezuela, together with the Latin America regional aggregate, underwent a “lost decade” (prolonged periods of stagnation), which highlights the confluence of the large COVID-19 shock and scarring effects with the underlying vulnerabilities that in many cases were built over several decades.

We examine how a more hawkish policy stance – defined as an above-median long-run inflation semi-elasticity of the policy rate – affects economic growth in 37 inflation-targeting (IT) countries. To this end, we estimate time-varying, bias-corrected forward-looking Taylor rules for all IT countries for which the data permit such estimation. Our results point to sizable growth effects, exceeding 0.8% annually, for countries with a more hawkish policy stance. This suggests that the growth benefits reported in the previous literature on inflation targeting are primarily driven by a small subset of countries that react more forcefully to inflation.

We analyze district‑level data for paddy, wheat, and millets (2010–2019) across India to identify yield hotspots with consistently high or rising productivity and coldspots with persistent declines. Spatial clustering and regression analyses show that weather, irrigation, fertilizer use, and farmers’ mobile-based information access shape yield performance. Coldspots produce roughly half the yield of hotspots due to lower input and information use. Hotspots cluster in north and southern India, while coldspots dominate the west, east, and northeast. Average yield gaps for paddy, wheat, and millets are 2.0, 2.4, and 1.0 t ha−1, respectively. Closing these gaps could substantially raise farm revenues.

The consensus view in the growth literature is that R&D scale effects are absent in mature industrialized economies but may be present in emerging economies undergoing transition. Scale effects imply a proportional relationship between a stationary $I(0)$ regressand (growth rates of real per capita GDP and/or TFP) and a non-stationary $I(1)$ regressor (the scale of R&D), which gives rise to the problem of unbalanced regression and spurious parameter estimates. This issue has not been adequately addressed in the existing literature. Furthermore, emerging economies have received relatively little attention in this context. We address these issues by (i) accurately measuring R&D scale and (ii) adopting an appropriate econometric specification and estimator. We find significant scale effects in a panel of emerging countries, but not in developed countries. We propose an endogenous growth model that captures these properties—presence of scale effects during growth transitions, but not at the long-run equilibrium—thereby reconciling our results. Our model predicts that the long-run growth rates of per capita real GDP and TFP are driven by the growth rates of technological innovation and aggregate employment—although, in the case of emerging economies, only technological innovation significantly contributes to TFP growth.

This paper explores the relationship between entrepreneurship, measured by the number of new firms per million inhabitants, and modern economic growth in Spain between 1886 and 2000. Following Audretsch and Keilbach’s methodology, our analysis seems to confirm that entrepreneurship has had a positive and statistically significant effect on GDP per capita and labor productivity. This finding challenges the traditional view that the entrepreneurial factor has hindered the country’s economic growth. Additionally, using data on the size and legal form of start-up firms, our results suggest that neither characteristic has been an important driver of Spain’s long-term economic growth. However, we find that the impact of both variables differs depending on the years studied. To our knowledge, this study is the first attempt to test econometrically the long-term contribution of entrepreneurship to Spain’s economic growth.

The established economic historiography asserts that Brazil’s per-capita GDP stagnated in the 19th century and that it grew extremely slowly in the period of the monarchy (1822–1889). We argue that these conclusions are based on inadequate methods, insufficient statistical evidence, and disregard for available historical evidence. Building on the methodology followed by one of us in a previous article, with the use of new databases, and a reasoned exploration of alternatives, our best estimate is that over the 1820–1900 period, Brazil’s per-capita income grew at a trend rate of 0.9% per year, a performance like Western Europe and other Latin America countries. Only a sharp economic contraction at the end of the period dulled Brazil’s performance in the 19th century.

This paper investigates the permanent effect on total factor productivity (TFP) of temporary shocks. We estimate a structural vector autoregression to test the predictions of endogenous growth models over the business cycle. According to theory, the stock of technological knowledge promotes its flow as researchers “stand on the shoulders of giants.” Therefore, if R&D investment is pro-cyclical—as data show and theory predicts—a recession leads to a temporary deviation of the R&D level from its trend, thus reducing new knowledge creation. The lost technological advancements cause the economy to follow a parallel but permanently lower growth path. Our findings align with the primary theoretical prediction. Quantitatively, the US economy forgoes approximately 1.3% in TFP following an increase in cyclical unemployment that peaks at 1 percentage point above the mean. The historical variance decomposition shows a strong positive effect during the boom of the late 1960s and strong negative effects around the Volcker disinflation period and the Great Recession. Finally, we estimate the effects on R&D of a TFP shock to differentiate between different explanations on how the R&D pro-cyclicality arises. Our results align with models where financial frictions or nominal rigidities drive it.

This paper investigates both conditional and unconditional convergence in labor productivity within the manufacturing industries of the Eurozone over the period 1963 – 2018. We employ two innovative models: constant and varying-coefficient hierarchical panel data convergence regression models, each equipped with two sets of latent factor structures—one comprising global factors and the other industry-specific factors. These models offer distinct advantages, allowing for both global and industry-specific cross-sectional dependencies and permitting parameter heterogeneity across individual industries. Our findings reveal both conditional and unconditional convergence across the manufacturing industry as a whole, as well as among the majority of the 23 sub-manufacturing industries at the ISIC two-digit level. Moreover, we observe significant variation in convergence dynamics among these sub-manufacturing industries. Robustness checks, performed across different subperiods, confirm the reliability of our results. Furthermore, a comparison of our model’s outcomes with those of two alternative models provides additional support for our conclusions.

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.

This paper builds on Hsieh and Klenow’s (2009) model to offer a refined analysis of how input misallocations impact aggregate total factor productivity (TFP). We enhance the original model by relaxing the assumption of uniform input prices and adopting an econometric approach to estimate parameters using firm-level data. Estimation of model parameters and allocation efficiency is based on the system of input demand and the production function. We use an indirect inference approach to estimate the system to avoid maximum likelihood estimation, which often faces convergence issues, when there are numerous constraints. We demonstrate our model using the US firm-level manufacturing panel data from 1975 to 2010. Our final sample contains 55,518 observations. We divide the manufacturing industry into seven major categories. Our findings indicate that between 1975 and 2010, the average productivity growth rate was 2.8% but could have reached 3.2% without misallocation, highlighting the substantial gains possible through better resource allocation.

The study analyzes productive efficiency of crop farming in the EU. We use publicly available data on crop farming from FADN database. Standard efficiency measurement techniques based on frontier analysis indicate that the representative farms provided in the database are fully efficient, even though there is ample evidence in the literature that this is highly unlikely. We find that this is a consequence of overly restrictive assumptions about the compound error in standard SF models. The efficiency benchmark, based on the best model given data with generalized error specification, reveals substantial differences in crop farming efficiency in the EU.

We explore the theoretical conditions in which natural capital improves explanations of aggregate income growth from factor changes. With positive total factor productivity (TFP) growth, including natural capital better explains growth if natural capital growth rates exceed physical capital growth rates. With negative TFP growth and higher natural capital growth rates, natural capital worsens explanations of growth. Using a comprehensive dataset on natural resource stocks and income shares in GDP, we perform an empirical analysis with 99 countries over three time periods between 2001 and 2015 and find that 41 per cent of country-time periods meet the conditions for improved growth explanation with natural capital. Of these, 59 per cent occur because TFP growth is negative, and physical capital growth exceeds that of natural capital. In these cases, including natural capital simultaneously reduces bias in factor shares and TFP estimates and improves the share of growth explained by changes in factors.

Relying upon an original (country-sector-year) measure of robotic capital ($RK$), we investigate the degree of complementarity/substitutability between robots and workers at different skill levels. We employ nonparametric methods to estimate elasticity of substitution patterns between $RK$ and skilled/unskilled labor over the period 1995–2009. We show that: i) on average, $RK$ exhibits less substitutability with skilled workers compared to unskilled workers, indicating a phenomenon of “RK-Skill complementarity”. This pattern holds in a global context characterized by significant heterogeneity; ii) the dynamic of “RK-Skill complementarity” has increased since the early 2000s; iii) the observed strengthening is more prominent in OECD countries, as opposed to non-OECD countries, and in the Manufacturing sector, compared to non-Manufacturing industries.

Labour productivity stagnated in the UK in the period between the financial crisis and the emergence of Covid-19. Labour supply and employment grew strongly over the same period, driven primarily by net inward migration. While labour productivity should be independent of labour supply in the long run, this need not be the case in the medium run while capital per worker adjusts. Exploiting a range of evidence, we conclude that around 4 pp of the estimated 20% shortfall in productivity from its previous trend that had emerged by 2019 might be explained by increased labour supply, with a slowdown in TFP growth accounting for most of the shortfall.

This paper investigates the nexus between per capita income convergence and political institutions within the Eurozone. Employing data spanning the years 2002–2019, the research initially identifies multiple convergence clusters and subsequently examines the relationship between the creation of these clusters and different aspects of political institutions. The findings reveal that there are multiple steady states in the Eurozone, and their formation is notably influenced by political institutions alongside other conventional economic determinants derived from the Solow model. Furthermore, the study underscores that improvements in regulatory quality, as well as in aspects such as democracy, government effectiveness, and corruption control, positively impact income convergence across all member countries. These findings carry significant policy implications.

Even at long time horizons, modern outcomes are in some sense bounded by history. Culture shapes how people interact and as it propagates across generations, groups with more common ancestors face less frictions to cooperation. This, in turn, affects institutional and technological diffusion, implying a society's history plays a crucial role in the causes of sustained long-run economic growth. To test this, we follow other studies by proxying for historical effects with genetic relatedness, which yields a temporal proportionality of shared common ancestry. Measuring cultural traits are more challenging. We develop a new systematic measure through network analysis of Wikipedia. Connectivity statistics over the encyclopaedia's hyperlink-directed network captures unique features of cultural relatedness. Further, as we index pages, we can coarsen the network into specific topics. The results show how history correlates broadly over a range of cultural factors. Differences across the coarsened networks demonstrate not simply that history matters, but where it matters less.

This paper assesses Brazil's real convergence (1822–2019) through unit root tests and Markov Regime-Switching (MS) models in three different scenarios: towards (i) other six Latin American countries (LA6); (ii) Portugal; and (iii) the technological frontier country, the US. The extended unit root test results favour Brazil's very long-run real convergence towards LA6 and Portugal, but not the US. The estimated MS models, involving two different regimes, real convergence and real non-convergence/divergence, capture institutional quality's positive effect in promoting Brazil's real convergence.