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The labor share may be declining in the data, but it is often assumed constant in neoclassical growth models (NGM). We assess the quantitative importance of this discrepancy by comparing alternative calibration approaches featuring constant and declining labor shares. We find little difference in model performance. Our results derive from strong general equilibrium effects: while a declining labor share mechanically lowers wage growth, the investment response pushes wages back up. Hence, different models deliver nearly identical paths of macro aggregates. Numerous robustness checks (including a CES production function, different time periods, and calculations of the labor share) reinforce the similarity of performance across model specifications. We conclude that the NGM with a constant labor share is still an appropriate choice to study many standard macro aggregates.

Training is essential not only to increase productivity, but also to keep workers of an organization motivated and inspired. In this study, the effectiveness of trainings conducted by Indian Council of Agricultural Research (ICAR) during 2017-18 in which 901 Scientists, 506 Technical, 519 Administrative and 313 Skilled Support Staff (SSS) from 106 ICAR-Institutes across 26 States/UTs participated was assessed by HRM Unit, ICAR HQs, New Delhi during 2018-19. Study revealed that the pooled perceived training effectiveness index (PTEI) was 3.86, referring medium effectiveness of trainings. The mean PTEI score was the highest for SSS (3.94) followed by Administrative staff (3.90). Overall, most of the participants (58.83%) reported medium degree of effectiveness of the training programmes. Behavioural changes and changes in practices as a consequence of exposure to the trainings are evident from the findings. The study revealed that perceived effectiveness was significantly associated with age, gender and duration of training programmes. Some observed constraints by the trainees were inadequate infrastructure at Institutes, sometimes lesser relevancy of few topics and lack of practical exposure. The major suggestions were inclusion of more practical sessions, follow up programmes for trainee-trainer meet, and increasing the duration of the trainings in few cases. The trainings organised by ICAR should continue for all staff categories to bring about desirable changes in competencies.

We measure gains from trade in multisector economies with nonhomothetic preferences where changes in trade costs generate reallocation of expenditure across sectors. We show how to measure the trade elasticity and how it relates to welfare. In this environment, the trade elasticity now varies both across countries and with levels of trade costs. In an application, we find that the trade elasticity varies substantially across countries and that the gains from moving from autarky to observed trade are on average between 24% and 28% greater than in a model where the trade elasticity is constant.

This paper considers whether a fairly well-established empirical relationship between liberalized trade and firm productivity growth is sensitive to the choice of an identification strategy for production function estimation. We estimate the productivity of Colombian manufacturing plants using the methods of Levinsohn and Petrin (2003), Ackerberg, Caves, and Frazer (2006), and Gandhi, Navarro, and Rivers (2012), and at times come to surprisingly different conclusions about the country's experience with trade policy reform during the 1980s. Results from a quantile regression model and a productivity growth decomposition exercise tend to vary as we experiment with different specifications of the production function. Research that is concerned with the short and medium-term impact of trade liberalization on domestic manufacturing industries should therefore pay close attention to issues of robustness to alternative strategies for estimating the productivity of firms.

Process‐based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass‐dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C3 grasses and (sub)tropical C4 grasses. Incorporation of species‐level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance‐related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage‐based functional types (LFTs), situated between species‐level trait data and PFT‐level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.

We study the impact of trade on a country catching up to the industrial leader. We calibrate our dynamic, two-country model to Spain and UK from 1850 to 2000, accounting for the inter-war trade collapse (IWTC) and the subsequent catch up by Spain. In our model, the effects of trade disruptions are stronger with more distance to the leader and more openness. A collapse today (less distance, more openness) similar to the IWTC (more distance, less openness) decreases the capital stock thrice as much (12% instead of 4%). Importantly, traded varieties would fall today but increased during the IWTC.

Grasslands dominated by taxa using the C4photosynthetic pathway first developed on several continents during the Neogene and Quaternary, long after C4photosynthesis first evolved among grasses. The histories of these ecosystems are relatively well-documented in the geological record from stable carbon isotope measurements (of fossil vertebrate herbivores and paleosols) and the plant microfossil record (pollen and/or phytolith assemblages). The distinct biogeography and ecophysiology of modern C3and C4grasses have led to hypotheses explaining the origins of C4grasslands in terms of long-term changes in the Earth system, such as increased aridity and decreasing atmospheric pCO2. However, quantitative proxies for key abiotic drivers of these hypotheses (e.g., temperature, precipitation, pCO2) are still in development, not yet widely applied at the continental or global scale or throughout the late Cenozoic, and/or remain contentious. Testing these hypotheses globally therefore remains difficult. To understand better the potential links between changes in the Earth system and the origin of C4grasslands, we undertook a global-scale comparison between observational records of C4plant abundances in Miocene and Pliocene localities compiled from the literature and three increasingly complex models of C4physiology, dominance, and abundance. The literature compilation comprises > 2,600 δ13C-values each of fossil terrestrial vertebrates and of paleosol carbonates, which we interpret as primarily proxies for the abundance of C4grasses, based on the modern contribution of C4grasses to terrestrial net primary productivity. We forced the vegetation models with simulated monthly climates from the HadCM3 family of coupled ocean-atmosphere general circulation models (OAGCMs) over a range of pCO2-values for each epoch to model C4dominance or abundance in grid cells as: (1) months per year exceeding the temperature at which net carbon assimilation is greater for C4than C3photosynthesis (crossover temperature model); (2) the number of months per year exceeding the crossover temperature and having sufficient precipitation for growth (≥25 mm/month; Collatz model); and (3) the Sheffield Dynamic Global Vegetation Model (SDGVM), which models multiple plant functional types (PFTs) (C3and C4grasses, evergreen, and deciduous trees). Model-data agreement is generally weak, although statistically significant for many comparisons, suggesting that regional to local ecological interactions, continent-specific plant evolutionary histories, and/or regional to local climatic conditions not represented in global scale OAGCMs may have been equally strong or stronger in driving the evolution of C4grasslands as global changes in the Earth system such as decreases in atmospheric pCO2and late Cenozoic global cooling and/or aridification.

Atkinson, Piketty, and Saez [2011] find a post-1979 surge in taxfiler top income shares in “English speaking countries” (surge countries) but not in “continental European countries and Japan” (no-surge countries). We find the puzzle that Comtrade import-to-GDP ratios and import-to-total-import ratios for apparent luxuries pearls, precious stones, diamonds, works of art, jewellery, furs and coins do not increase post-1979 in surge countries relative to no-surge countries. Explanations could include issues with the taxfiler or import data or that top income individuals do not have a particularly high marginal to propensity to consume these luxury goods, at least within their own country. Overall, this is a fragment of evidence that there may not have been a large post-1979 increase in top-end domestic consumption inequality in surge countries compared to no-surge countries.

Applied general equilibrium (AGE) models, which feature multiple countries, multiple industries, and input–output linkages across industries, have been the dominant tool for evaluating the impact of trade reforms since the 1980s. We review how these models are used to perform policy analysis and document their shortcomings in predicting the industry-level effects of past trade reforms. We argue that, to improve their performance, AGE models need to incorporate product-level data on bilateral trade relations by industry and better model how trade reforms lower bilateral trade costs. We use the least-traded-products methodology of Kehoe et al. (2015) to provide guidance on how improvements can be made. We provide further suggestions on how AGE models can incorporate recent advances in quantitative trade theory to improve their predictive ability and better quantify the gains from trade liberalization.

Total Factor Productivity (TFP) growth in Canada between 2002 and 2014 has been only 0.16% per year. Although many developed countries have experienced a productivity slowdown since the beginning of the century, this figure is still substantially smaller than that of the U.S. We perform multiple counterfactual exercises to show that this difference in TFP growth cannot be accounted for by several compositional effects and/or mismeasurements of factors of production. We identify two key sectors (Mining and Manufacturing) that drive all of the TFP growth difference with the U.S. Despite the lack of TFP growth, Canada has experienced sustained income growth due to a prolonged period of appreciation of the terms of trade (while terms of trade in the U.S. have deteriorated), making real income in the two countries grow at similar rates.

We study a labor market where firms have private information about their ex-ante heterogeneous productivities and search is random. In this environment, a binding minimum wage can be efficiency-enhancing - we show that setting it using a version of the Vickery-Clarke-Groves mechanism delivers full efficiency. In a dynamic, stochas-tic version of the model calibrated to the Routine Manual labor market in the U.S., our proposed mechanism generates sizeable welfare gains. The resulting minimum wage is procyclical, dampening the response of unemployment to aggregate shocks.

We measure the gains from a trade cost reduction in a model with dynamic accumulation of factors. We show that the tight link between import intensity and gains from trade that exists in static models breaks down along transition paths in dynamic models. When trade costs are reduced, the need to accumulate factors temporarily shifts spending from consumption to investment. Import intensity may rise or fall along the transition path, depending on the relative import intensity of consumption and investment. Calibrating the model to the U.S. economy, we find that investment is more import intensive than consumption, so that import intensity is falling along the transition path even as consumption is rising. Therefore, while higher import intensity is associated with higher consumption when comparing steady states (as in static models), it is associated with lower consumption along a given transition path. We also consider the case of endogenous firm creation as another form of investment and factor accumulation, and again find a negative relationship between consumption and import intensity along the transition path.