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

Distributed drone base station positioning for emergency cellular networks using reinforcement learning

Due to the unpredictability of natural disasters, whenever a catastrophe happens, it is vital that not only emergency rescue teams are prepared, but also that there is a functional communication network infrastructure. Hence, in order to prevent additional losses of human lives, it is crucial that network operators are able to deploy an emergency infrastructure as fast as possible. In this sense, the deployment of an intelligent, mobile, and adaptable network, through the usage of drones—unmanned aerial vehicles—is being considered as one possible alternative for emergency situations. In this paper, an intelligent solution based on reinforcement learning is proposed in order to find the best position of multiple drone small cells (DSCs) in an emergency scenario. The proposed solution’s main goal is to maximize the amount of users covered by the system, while drones are limited by both backhaul and radio access network constraints. Results show that the proposed Q-learning solution largely outperforms all other approaches with respect to all metrics considered. Hence, intelligent DSCs are considered a good alternative in order to enable the rapid and efficient deployment of an emergency communication network

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

Churning and Profitability in the U.S. Corporate Sector

This paper establishes that entry and exit regulate the top half of the profitability distribution in the post-1970 U.S. economy. We, first, document stability in the distribution of total profits earned on tangible, intangible, and financial capital. Whereas a narrower measure of returns on tangible capital, instead, suggests rising dispersion, it fails to capture post-1970 growth in intangible and financial assets. Second, we use quantile decompositions to show that churning – specifically, exit for cause – regulates median and top-end profitability. Thus, the process by which competition drives out unprofitable firms acts to stabilize profit rates in the U.S. economy

Energy efficiency-spectral efficiency trade-off of transmit antenna selection

We investigate the energy efficiency-spectral efficiency (EE-SE) trade-off of transmit antenna selection/maximum ratio combining (TAS) scheme. A realistic power consumption model (PCM) is considered, and it is shown that using TAS can provide significant energy savings when compared to multiple-input multiple-output (MIMO) in the low to medium SE region, regardless the number of antennas, as well as outperform transmit beamforming scheme (MRT) for the entire SE range. For a fixed number of receive antennas, our results also show that the EE gain of TAS over MIMO becomes even greater as the number of transmit antennas increases. The optimal value of SE that maximizes the EE is obtained analytically, and confirmed by numerical results. Moreover, the influence of receiver correlation is also evaluated and it is shown that considering a non-realistic PCM can lead to mistakes when comparing TAS and MIMO

The Dynamic Hedging Effectiveness for Soybean Farmers of Mato Grosso with Futures Contracts of BM&F

Paper presented in the VII PENSA CONFERENCE, November/2009, FEA/USP, São Paulo, Brazil.Dynamic hedge, effectiveness, soybeans, Mato Grosso, Agribusiness, Marketing,