A new professionalism for agricultural research for development

There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies. In this paper, we share learning from efforts to mainstream such an approach through a large, multi-partner CGIAR research program working in aquatic agricultural systems. We reflect on four years of implementing research in development (RinD), the program’s approach to the new professionalism. We highlight successes and challenges and describe the key characteristics that define the approach. We conclude it is possible to build a program on a broader approach that embraces multidisciplinarity and engages with stakeholders in social-ecological systems. Our experience also suggests caution is required to ensure there is the time, space and appropriate evaluation methodologies in place to appreciate outcomes different to those to which conventional agricultural research aspires.     

The Impact of Technology Accumulation on Technical Efficiency: An Analysis of the Sri Lankan Clothing and Agricultural Machinery Industries

This paper examines the effects of technology accumulation on firm-level technical efficiency in the Sri Lankan clothing and agricultural machinery industries, using cross-section survey data. Econometric analysis of the economic effects of technology development in developing countries is limited and this paper seeks to address this gap in the literature. The analysis shows simple adaptive technical change to have a significant and positive effect on efficiency in both industries. In addition, variables relating to technological skills and training also emerge as significant determinants of firm-level efficiency.     

Intellectual capital and firm performance: evidence from Indian banking sector

In the aftermath of the 2008 financial crisis, the entire Indian banking industry was paralysed and their performance was shattered by the unfolding of enormous cases of Non-performing Assets (NPA). The study estimates the operating efficiency of 40 Indian banks for 5 years (2011–15) as a proxy of performance measure using the output-oriented DEA-BCC model. We find that nearly 62% of the state-owned banks and 47% of the private banks are inefficient indicating that the inefficient banks need to reduce their inputs or improve their output to become efficient. The study further investigates the relationship between intellectual capital (IC) and bank performance using a truncated regression model. The regression results show that out of the three components of intellectual capital, only human capital efficiency is positively and significantly associated with operational efficiency while structural capital and finance capital have a negative impact on the efficiency of banks. The study concludes that to achieve competitive edge banks should invest in their human capital. The results are robust in the case of financial variables taken as a proxy for performance.     

Segregación por género en el sector manufacturero formal de la India

Mediante el cálculo de un índice de disimilitud con datos de la Encuesta Anual de Industrias, los autores constatan que la segregación por género en las manufacturas indias entre 1989–1990 y 2000–2001 disminuyó, aunque debido sobre todo a cambios en la estructura sectorial del empleo, y no tanto a la integración de género. El índice resultó sensible al número de grupos de industrias establecido en la clasificación utilizada para el cálculo. Tanto a escala nacional como estatal, las mujeres tienen muy pocas oportunidades de empleo formal, concentradas en ciertos sectores manufactureros tradicionalmente femeninos, como los de alimentos, tabaco, confección, hilado y textil.     

Financial Distress in the Great Depression

We use firm‐level data to study corporate performance during the Great Depression era for all industrial firms on the NYSE. Our goal is to identify the factors that contribute to business insolvency and valuation changes during the period 1928‐1938. We find that firms with more debt and lower bond ratings in 1928 became financially distressed more frequently during the Depression, consistent with the trade‐off theory of leverage and the information production role of credit rating agencies. We also document for the first time that firms responded to tax incentives to use debt during the Depression era but that the extra debt used in response to this tax‐driven “debt bias” did not contribute significantly to the occurrence of distress. Finally, we conduct an out‐of‐sample test during the recent 2008‐2009 Recession and find that higher leverage and lower bond ratings also increased the occurrence of financial distress during this period.     

Inventories and antidumping: the case of orange juice trade

The United States and Brazil are key players in the international market for orange juice, mainly frozen concentrated orange juice (FCOJ). The U.S. orange juice industry benefits from one of the highest levels of import protection in U.S. agriculture. Additional trade protection was recently added with a U.S. industry victory in an antidumping trade suit against Brazil. We study the impact of FCOJ imports from Brazil on U.S. prices using time series econometric models and find only a weak FCOJ domestic price response to imports from Brazil, because extremely large U.S. inventories mute the price impact of any fluctuation in imports. Our findings imply that the antidumping tariffs were unjustified based on a material injury argument.     

Technological upgrading and energy demand scenarios for Indian railways—A system dynamics study

This paper presents a system dynamics model of the Indian railway system and generates probable scenarios of its performance up to the year 2011. The basic structure of the model, the relationships between the interacting variables, and the generic flow diagrams used for developing the model are discussed in detail. In generating the scenarios, probable changes in the railway system and in the national socioeconomic environment in which it works are considered. In particular, introduction of technological innovations in the railways and their impact on railway energy demand are examined in detail.     

Predicting Downturns in the US Housing Market: A Bayesian Approach

This paper estimates Bayesian Vector Autoregressive (BVAR) models, both spatial and non-spatial (univariate and multivariate), for the twenty largest states of the US economy, using quarterly data over the period 1976:Q1–1994:Q4; and then forecasts one-to-four quarters-ahead real house price growth over the out-of-sample horizon of 1995:Q1–2006:Q4. The forecasts are evaluated by comparing them with those from an unrestricted classical Vector Autoregressive (VAR) model and the corresponding univariate variant of the same. Finally, the models that produce the minimum average Root Mean Square Errors (RMSEs), are used to predict the downturns in the real house price growth over the recent period of 2007:Q1–2008:Q1. The results show that the BVARs, in whatever form they might be, are the best performing models in 19 of the 20 states. Moreover, these models do a fair job in predicting the downturn in 18 of the 19 states.     

Exchange Rate Exposure and its Determinants: Evidence from Indian Firms

This article examines the determinants of the exchange rate exposure by comparing both manufacturing and service sector firms in India over the period of 2000 to 2013. First, the study finds that service sector firms are more exposed to exchange rate changes than manufacturing firms in India. Second, the results indicate that the market-to-book ratio and export are significant and positively related; however, size is negatively related to the exchange rate exposure of both the manufacturing and service sector firms. These results are robust with the estimation using a trade-weighted exchange rate.