Growth Complementarity Between Agriculture and Industry: Evidence from a Panel of Developing Countries

Abstract: Using dynamic panel models with data for 62 developing countries, this paper examines whether growth in agriculture elicits growth in manufacturing. For identification, I use population-weighted, average temperature as an instrument for growth in agriculture. I identify large short-run effects: An increase in growth in agriculture by one percentage point is estimated to raise contemporaneous growth in manufacturing by between 0.47 and 0.56 percentage points. The baseline models also imply sizable long-run effects of permanent increases in growth in agriculture. Extensions of the empirical model suggest that growth in agriculture benefits the manufacturing sector by improving its domestic terms of trade, by increasing the share of investment and saving in GDP, and by increasing the capacity to import industrial inputs. The paper makes two main contributions. First, it joins a growing literature using climate data to identify supply shocks in agriculture, establishing a robust empirical relation between these shocks and growth in manufacturing. Second, it includes a stylized two-sector model to illuminate the macroeconomic channels behind this complementarity. Together, these contributions lend support to the notion that agriculture plays key macroeconomic roles in the industrialization of developing countries by relieving saving, aggregate demand, _scale, and foreign exchange constraints on the industrial sector

Essays on Growth Complementarity Between Agriculture and Industry in Developing Countries

This dissertation examines three aspects of the macroeconomic role of agriculture in the industrialization of developing countries. In the first essay, I utilize instrumental variable techniques to empirically identify the effect of growth in agriculture on growth in manufacturing. Using data for 62 countries and instrumental variable techniques, I find that higher land yields in agriculture raise growth in manufacturing in the short to medium run. Along with extensions of the basic empirical model, this finding suggests that land-saving technical change can stimulate demand for industrial goods, raise fiscal revenues, and provide foreign exchange earnings to finance capital accumulation. In the second essay, I examine the role of biased-technical change in agriculture in the formation of aggregate demand for industry. I use a two-sector growth model to show that, under conditions of low factor substitutability and hidden unemployment, land-saving innovations can raise rural employment, enlarge the domestic market for manufactures, and promote faster industrial accumulation --- in contrast to labor-saving innovations. I also develop saving-constrained and open economy extensions of the baseline model. The essay casts light on a recent strand of empirical studies --- including the first essay of this dissertation --- which have identified a positive impact of higher land yields on industrial growth. Finally, in the third essay I develop a political-economic explanation for the labor-displacing trend that existed across the larger and most dynamic agricultural establishments in Brazil during the 1950-1980 period. Using primary data and the secondary literature, I document this trend and argue that it resulted from the interaction between public policies to promote the use of modern inputs, on the one hand, and size and power inequality across landholdings, on the other hand. As a result, the pattern of technical change in agriculture aggravated the problem of underemployment that beset Brazil\u27s industrialization, preventing a broader distribution of its benefits

Real Wages and Labor-saving Technical Change: Evidence from a Panel of Manufacturing Industries in Mature and Labor-surplus Economies

This paper uses panel cointegration and error correction models to unveil the direction of long-run causality between the real product wage and labor productivity at the industry level. I use two datasets of manufacturing industries: the EU-Klems dataset covering 11 industries in 19 developed economies, and the Unido Industrial Statistics Database covering 22 industries in 30 developed and developing economies. In both datasets, I find evidence of cointegration between the two variables, as well as evidence of two-way, long-run Granger causality. These findings are consistent with theories of directed technical change, which claim that a rise in labor costs sparks the adoption of labor-saving innovations. They are also consistent with distributive theories whereby real wages keep apace of labor productivity growth, giving rise to long-run stability in functional distribution

An empirical analysis of Minsky regimes in the US economy

In this paper we analyze Minskian dynamics in the US economy via an empirical application of Minsky’s financing regime classifications to a panel of nonfinancial corporations. First, we map Minsky’s definitions of hedge, speculative and Ponzi finance onto firm-level data to describe the evolution of Minskian regimes. We highlight striking growth in the share of Ponzi firms in the post-1970 US, concentrated among small corporations. This secular growth in the incidence of Ponzi firms is consistent with the possibility of a long wave of increasingly fragile finance in the US economy. Second, we explore the possibility of short-run Minskian dynamics at a business-cycle frequency. Using linear probability models relating firms’ probability of being Ponzi to the aggregate output gap, which captures short-term macroeconomic fluctuations exogenous to individual firms, we find that aggregate downturns are correlated with an al- most zero increased probability that firms are Ponzi. This result is corroborated by quantile regressions using a continuous measure of financial fragility, the interest coverage ratio, which identify almost zero effects of short-term fluctuations on financial fragility across the interest coverage distribution. Together, these results speak to an important question in the theoretical literature on financial fragility regarding the duration of Minskian cycles, and lend support, in particular, to the contention that Minskian dynamics may take the form of long waves, but do not operate at business cycle frequencies

The Empirical Analysis of Minsky Regimes in the U.S. Economy

In this paper we analyze Minskian dynamics in the US economy via an empirical application of Minsky’s financing regime classifications to a panel of nonfinancial corporations. First, we map Minsky’s definitions of hedge, speculative and Ponzi finance onto firm-level data to describe the evolution of Minskian regimes. We highlight striking growth in the share of Ponzi firms in the post-1970 US, concentrated among small corporations. This secular growth in the incidence of Ponzi firms is consistent with the possibility of a long wave of increasingly fragile finance in the US economy. Second, we explore the possibility of short-run Minskian dynamics at a business-cycle frequency. Using linear probability models relating firms’ probability of being Ponzi to the aggregate output gap, which captures short-term macroeconomic fluctuations exogenous to individual firms, we find that aggregate downturns are correlated with an almost zero increased probability that firms are Ponzi. This result is corroborated by quantile regressions using a continuous measure of financial fragility, the interest coverage ratio, which identify almost zero effects of short-term fluctuations on financial fragility across the interest coverage distribution. Together, these results speak to an important question in the theoretical literature on financial fragility regarding the duration of Minskian cycles, and lend support, in particular, to the contention that Minskian dynamics may take the form of long waves, but do not operate at business cycle frequencies

Estudo do envelhecimento dos ligantes asfálticos a partir do Modelo de Arrhenius

RESUMOO fenômeno do “envelhecimento” é responsável por modificar características do ligante asfáltico e da mistura asfáltica, gerando uma redução no ciclo de vida da camada. Diante disso, com a finalidade de minimizar a ação nociva a este fenômeno e garantir o ciclo de vida correta do pavimento, este trabalho traz a simulação de envelhecimento em curto prazo, analisando três características distintas, de acordo com modelo de Arrhenius. A partir dos dados obtidos, foi possível produzir curvas para o controle de qualidade, consideradas importantes ferramentas para controlar o tempo e temperatura durante os ciclos de produção, espalhamento e compactação da mistura de asfáltica. Desta forma, a partir da análise da exposição do CAP 50/70 a várias temperaturas, foi possível determinar qual o seria o tempo máximo de exposição de modo a garantir que suas características físicas e reológicas permanecessem de acordo com os padrões mínimos estabelecidos pelas normas técnicas vigentes.Palavras-chave: ligantes asfálticos; envelhecimento; Modelo de Arrhenius. ABSTRACTThe phenomenon of "aging" is responsible for modifying characteristics of the asphalt binder and asphalt mixture, resulting in a decrease in the layer lifecycle. Therefore, in order to minimize the harmful effects of this phenomenon and ensure the correct life cycle of the pavement, this work brings in short-term aging simulation, analyzing three distinct characteristics, according to Arrhenius model. From the data obtained, it was possible to produce curves for quality control, considered important tools to control the time and temperature during production cycles, spreading and compacting the asphalt mixture. Thus, from the analysis of the exposure of the CAP 50/70 at various temperatures, it was possible to determine which would be the maximum exposure time to ensure that their physical and rheological properties remain in accordance with the minimum standards established by technical standards current.Keywords: Asphalt binders; Aging; Arrhenius model. RESUMENEl fenómeno de "envejecimiento" es responsable de la modificación de características de la mezcla de aglutinante de asfalto y el asfalto, lo que resulta en una disminución en el ciclo de vida de capa. Por lo tanto, con el fin de minimizar los efectos nocivos de este fenómeno y garantizar el ciclo de vida correcto del pavimento, este trabajo aporta en la simulación de envejecimiento de corto plazo, el análisis de tres características distintas, según el Modelo de Arrhenius. De los datos obtenidos, era posible producir curvas de control de calidad, considerada herramientas importantes para controlar el tiempo y la temperatura durante los ciclos de producción, difusión y compactación de la mezcla de asfalto. Por lo tanto, a partir del análisis de la exposición de la PAC 50/70 a diversas temperaturas, fue posible determinar cuál sería el tiempo máximo de exposición para asegurar que sus propiedades físicas y reológicas se mantienen de acuerdo con las normas mínimas establecidas por las normas técnicas vigor.Palabras clave: ligantes asfálticos; envejecimiento; Modelo de Arrhenius

Genetic Diversity Strategy For The Management And Use Of Rubber Genetic Resources: More Than 1,000 Wild And Cultivated Accessions In A 100-genotype Core Collection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)The rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Muell. Arg.] is the only plant species worldwide that is cultivated for the commercial production of natural rubber. This study describes the genetic diversity of the Hevea spp. complex that is available in the main ex situ collections of South America, including Amazonian populations that have never been previously described. Genetic data were analyzed to determine the genetic structure of the wild populations, quantify the allelic diversity and suggest the composition of a core collection to capture the maximum genetic diversity within a minimal sample size. A total of 1,117 accessions were genotyped with 13 microsatellite markers. We identified a total of 408 alleles, 319 of which were shared between groups and 89 that were private in different groups of accessions. In a population structure and principal component analysis, the level of clustering reflected a primary division into the following two subgroups: cluster 1, which consisted of varieties from the advanced breeding germplasm that originated from the Wickham and Mato Grosso accessions; and cluster 2, which consisted of the wild germplasm from the Acre, Amazonas, Para and Rondonia populations and Hevea spp. The analyses revealed a high frequency of gene flow between the groups, with the genetic differentiation coefficient (GST) estimated to be 0.018. Additionally, no distinct separation among the H. brasiliensis accessions and the other species from Amazonas was observed. A core collection of 99 accessions was identified that captured the maximum genetic diversity. Rubber tree breeders can effectively utilize this core collection for cultivar improvement. Furthermore, such a core collection could provide resources for forming an association panel to evaluate traits with agronomic and commercial importance. Our study generated a molecular database that should facilitate the management of the Hevea germplasm and its use for subsequent genetic and genomic breeding.107Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)FAPESP [2007/50392-1, 2012/50491-8, 2011/50188-0, 2009/52975-0, 2012/05473-1]CNPq [478701/2012-8, 402954/2012-2

Fire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons

Wildfires expose populations to increased morbidity and mortality due to increased air pollutant concentrations. Data included burned area, particulate matter (PM10, PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, relative humidity, wind-speed, aerosol optical depth (AOD) and mortality rates due to Circulatory System Disease (CSD), Respiratory System Disease (RSD), Pneumonia (PNEU), Chronic Obstructive Pulmonary Disease (COPD), and Asthma (ASMA). Only the months of the 2011-2020 wildfire season (June-July-August-September-October) with burned area greater than 1000 ha were considered. Multivariate statistical methods were used to reduce the dimensionality of the data to create two fire-pollution-meteorology indices (PBI, API), which allow us to understand how the combination of these variables affect cardio-respiratory mortality. Cluster analysis applied to PBI-API-Mortality divided the data into two Clusters. Cluster 1 included the months with lower temperatures, higher relative humidity, and high PM10, PM2.5, and NO2 concentrations. Cluster 2 included the months with more extreme weather conditions such as higher temperatures, lower relative humidity, larger forest fires, high PM10, PM2.5, O3, and CO concentrations, and high AOD. The two clusters were subjected to linear regression analysis to better understand the relationship between mortality and the PBI and API indices. The results showed statistically significant (p-value < 0.05) correlation (r) in Cluster 1 between RSDxPBI (rRSD = 0.539), PNEUxPBI (rPNEU = 0.644). Cluster 2 showed statistically significant correlations between RSDxPBI (rRSD = 0.464), PNEUxPBI (rPNEU = 0.442), COPDxPBI (rCOPD = 0.456), CSDxAPI (rCSD = 0.705), RSDxAPI (rCSD = 0.716), PNEUxAPI (rPNEU = 0.493), COPDxAPI (rPNEU = 0.619).The work is funded by national funds through FCT - Fundação para a Ciência e Tecnologia, I.P.,596 in the framework of the ICT project with the references UIDB/04683/2020 and UIDP/04683/2020,597 and by the CILIFO (0753_CILIFO_5_E), FIREPOCTEP (0756_FIREPOCTEP_6_E) and598 TOMAQAPA (PTDC/CTAMET/29678/2017) projects

A Eficiência das Varas Cíveis do Distrito Federal: aplicação da análise de cluster e análise envoltória de dados / Efficiency of the Civil Courts of the Federal District: an application of the cluster analysis and data envelopment analysis

O Tribunal de Justiça do Distrito Federal e Territórios possui atualmente 53 Varas Cíveis em todo o Distrito Federal. Tendo em vista o crescente volume de processos peticionados por essa corte, faz-se necessária a constante busca pela eficiência na utilização dos recursos dessas Varas para a condução dos processos judiciais. Baseado na aplicação da ferramenta Data Envelopment Analysis (DEA), que é uma técnica não paramétrica de pesquisa operacional utilizada para mensuração de eficiências relativas, este trabalho busca uma forma adequada de aplicar esta metodologia com o objetivo de identificar possibilidades de melhorias nas eficiências das Varas Cíveis do Distrito Federal. Tendo em vista a heterogeneidade dos dados utilizados, optou-se pela segmentação das Varas Cíveis por meio da aplicação da análise de cluster e foi verificado se esta análise obteve resultados melhores que a aplicação do DEA sem o cluster. Como resultado, notou-se que a combinação entre o DEA e análise de cluster teve melhor êxito na identificação de possíveis ineficiências