nep-eff New Economics Papers
on Efficiency and Productivity
Issue of 2016‒08‒14
eight papers chosen by



  1. Evaluating Scale and Technical Efficiency among Farms and Ranches with a Local Market Orientation By Bauman, Allison; Jablonski, Becca B.R.; Thilmany McFadden, Dawn
  2. Efficiency in Production By Smallholder Rice Farmers Under Cooperative Irrigation Schemes in Pwani and Morogoro Regions, Tanzania By Joseph Kangile, Rajabu
  3. Analysing the Impact of Climate Change on Cotton Productivity in Punjab and Sindh, Pakistan By Raza, Amar; Ahmad, Munir
  4. Production Function Estimation with Measurement Error in Inputs By Allan Collard-Wexler; Jan De Loecker
  5. An Analysis of Institutional Credit, Agricultural Policy and Investment to Agriculture in India By saravanan, saravanan
  6. Impact of Farm Households’ Adaptation on Agricultural Productivity: Evidence from Different Agro-ecologies of Pakistan By Iqbal, Muhammad; Ahmad, Munir; Mustafa, Ghulam
  7. Agri-environmental measures and farmers’ rent: evaluating the potential contribution of auctions to increase the efficiency of Agri-environmental schemes in Emilia-Romagna (Italy) By Vergamini, Daniele; Viaggi, Davide; Raggi, Meri
  8. Estimating the Technology of Children's Skill Formation By Francesco Agostinelli; Matthew Wiswall

  1. By: Bauman, Allison; Jablonski, Becca B.R.; Thilmany McFadden, Dawn
    Abstract: In recent years, the growth in local food marketing channels has been significant. Most of the research in this field examining the economic implication of these trends has focused post-farmgate including supply chain analysis (e.g. Hardesty et al., 2014; King et al., 2010), regional economic impacts (e.g. Brown et al., 2014; Hughes et al., 2008; Jablonski et al., 2016), and consumer values and motivations that have driven demand (e.g. Costanigro, 2014; Lusk and Briggeman, 2009). To date, with the exception of a few case studies examining expenses and sales by channel assessment (LeRoux et al., 2010; Hardesty and Leff, 2010; Jablonski and Schmit 2016) there has been little research that examines the impact on financial viability among farms selling through these markets. The goal of this paper is twofold: first, to identify the factors that have the greatest influence on the efficiency of farmers and ranchers that participate in local food systems, and second, to estimate the relationship between marketing strategy and farm financial efficiency, with a particular focus on variations across farm size. Our estimation of the stochastic production frontier suggests that scale, production enterprise specialty, market outlet choices, land ownership, and management of expenses have the greatest influence on producer financial efficiency. Our model suggests that scale has the largest impact on financial efficiency, providing evidence that, all else constant, the most important factor in the efficiency of direct market producers is scale. When profit is defined as operating profit, results indicate that marketing channel is not an important indicator of efficiency. But when profit is defined as return on assets, marketing channel is an important indicator of efficiency, albeit less than is scale. Results from this analysis indicate there are economies of scale associated with farms and ranches that sell through local and regional markets, and that scale rather than marketing channel has the largest influence on efficiency.
    Keywords: Local foods, technical efficiency, farm profitability, Agribusiness, Farm Management, Productivity Analysis,
    Date: 2016
    URL: http://d.repec.org/n?u=RePEc:ags:aaea16:242364&r=eff
  2. By: Joseph Kangile, Rajabu
    Abstract: A DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN AGRICULTURAL AND APPLIED ECONOMICS OF SOKOINE UNIVERSITY OF AGRICULTURE. MOROGORO, TANZANIA. Advisor: Dr. Z. T. Mpenda
    Keywords: Crop Production/Industries, Environmental Economics and Policy, Farm Management, Production Economics,
    Date: 2015
    URL: http://d.repec.org/n?u=RePEc:ags:cmpart:243447&r=eff
  3. By: Raza, Amar; Ahmad, Munir
    Abstract: The study analyses the impact of climate change on productivity of cotton in Pakistan using the district level disintegrated data of yield, area, fertilizer, climate variables (temperature and precipitation) from 1981-2010. Twenty years moving average of each climate variable is used. Production function approach is used to analyse the relationship between the crop yield and climate change. This approach takes all the explanatory variables as exogenous so the chance endogenity may also be minimized. Separate analysis for each province (Punjab and Sindh) is performed in the study. Mean temperature, precipitation and quadratic terms of both variables are used as climatic variables. Fixed Effect Model, which is also validated by Hausman Test, was used for econometric estimations. The results show significant impact of temperature and precipitation on cotton yields. The impacts of climate change are slightly different across provinces— Punjab and Sindh. The negative impacts of temperature are more striking for Sindh. The impacts of physical variables—area, fertilizer, P/NPK ration and technology, are positive and highly significant. The results imply educating farmers about the balance use of fertilizer and generating awareness about the climate change could be feasible and executable strategies to moderate the adverse impacts of climate change to a reasonable extent.
    Keywords: Climate Change, Cotton Productivity, Production Function, Fixed Effect Model, Linear Effects and Marginal Effects
    JEL: Q15
    Date: 2015
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:72867&r=eff
  4. By: Allan Collard-Wexler; Jan De Loecker
    Abstract: Production functions are a central component in a variety of economic analyzes. However, these production functions often first need to be estimated using data on individual production units. There is reason to believe that, more than any other input in the production process, there are severe errors in the recording of capital stock. Thus, when estimating production functions, we need to account for the ubiquity of measurement error in capital stock. This paper shows that commonly used estimation techniques in the productivity literature fail in the presence of plausible amounts of measurement error in capital. We propose an estimator that addresses this measurement error, while controlling for unobserved productivity shocks. Our main insight is that in- vestment expenditures are informative about a producer’s capital stock, and we propose a hybrid IV-Control function approach that instruments capital with (lagged) investment, while relying on standard intermediate input demand equations to offset the simultaneity bias. We rely on a series of Monte Carlo simulations and find that standard approaches yield downward-biased capital coefficients, while our estimator does not. We apply our estimator to two standard datasets, the census of manufacturing firms in India and Slovenia, and find capital coefficients that are, on average, twice as large.
    JEL: D2 L1 O4
    Date: 2016–07
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:22437&r=eff
  5. By: saravanan, saravanan
    Abstract: Credit is an essential factor to determine the production and productivity in agriculture. For providing credit in India both Institutional sectors (Cooperative Banks, Commercial Banks and Regional Rural Banks) and non- Institutional sectors like money lenders, traders, landlords and relatives play significant. In order to increase the flow of credit the government of India introduced agriculture policy in 2004 to multiple credit to the farmers. At the same time, the role of both private and public sectors also contributes for agriculture in India. The cob-douglas production was used to determine the impact of institutional credit to agriculture GDP. In the cobb- douglas production function with agricultural GDP as dependent variable and institutional credit, net irrigated area, consumption of pesticide and consumption of fertilizer are independent variables. It was found that both institutional credit and net irrigated area had significant variables and other two variables are not significant.
    Keywords: Institutions, Credit, Policy, Investment
    JEL: Q13
    Date: 2016–08–05
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:72891&r=eff
  6. By: Iqbal, Muhammad; Ahmad, Munir; Mustafa, Ghulam
    Abstract: This study has utilised the Climate Change Impact Survey (CCIS, 2013) data and applied Treatment Effect Model (Heckman type) to analyse the impact of identified adaptation strategies if implemented in isolation or as portfolio (package of two or more) strategies on net revenue earned from wheat production in Pakistan. The implementation of adaptation strategies including varietal change, delayed sowing, and input intensification effect net revenues positively and significantly if adopted separately or as a part of portfolio strategies. Interestingly, the portfolio adaptation strategies missing delayed sowing resulted in either insignificant results or in reduced net revenues from wheat production. The evidence is found temperature (Nov-Dec.) and precipitation (March-April) norms and deviations of Jan-Feb. temperature from norm of the period are important determinants of net revenue. The results are supportive that fertility of land, farmer’s tenancy status, size of holding, non-farm income, and access to certain extension source are important determinants in the selection of various adaptation strategies. The study suggests revisiting the recommendations regarding wheat sowing dates by agricultural research institutions.
    Keywords: Climate Change, Adaptations, Wheat, Productivity
    JEL: Q15
    Date: 2015
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:72863&r=eff
  7. By: Vergamini, Daniele; Viaggi, Davide; Raggi, Meri
    Abstract: This work compares the cost-effectiveness of a simulated auction model (AM) with that of classical payment mechanisms as a marginal flat rate payment (MFR) and average flat rate payment (FR). The study provide an extension of the one-shot budget constrained auction model (BC) first introduced by Latacz-Lohmann and Van Der Hamsvoort (1997), and subsequently by Viaggi et al. (2008) and Glebe (2008). In this formulation, the model allows farmers to offer multi-dimensional bid as a combination of payment and a measure of a share of their land to commit to a hypothetical agri-environmental measure (AEM). The results show that the performance of the auction (i.e. 7.5 % and 27 % of the total UAA of the sample) is always located halfway between that of FR (i.e. 5% and 21 % of the total UAA of the sample) and that of MFR (i.e. 17% and 100% of the total UAA of the sample). According with Schillizzi and Latacz-Lohmann (2007) the flat rate option provides an amount of rents that is one and a half the auction’s rents with a lower budget and around two times greater with the higher budget level. The results confirm that the auction has the potential to reduce farmers’ information rent when compared with uniform policy instruments. However, the scale of saving depends crucially on auction design hypotheses and farmers' expectation about the maximum acceptable bid cap. The results of this research while attempting to provide a useful empirical exploration of auction theory cannot provide a comprehensive solution in most real world settings. However, it can contribute to feed the debate at EU policy level about the role of tendering instruments in agri-environmental programs to reduce the inefficiency related to the actual agri-environmental payments.
    Keywords: agri-environmental policy, conservation auction, compensation payments, information asymmetry, adverse selection, Agricultural and Food Policy, Environmental Economics and Policy, Q18, Q58,
    Date: 2016–06–17
    URL: http://d.repec.org/n?u=RePEc:ags:aiea16:242443&r=eff
  8. By: Francesco Agostinelli; Matthew Wiswall
    Abstract: We develop a new estimator for the process of children's skill formation in which children's skills endogenously develop according to a dynamic latent factor structure. Rather than assuming skills are measured perfectly by a particular measure, we accommodate the variety of skills measures used in practice and allow latent skills to be measured with error using a system of arbitrarily located and scaled measures. For commonly estimated production technologies, which already have a known location and scale, we prove non-parametric identification of the primitive production function parameters. We treat the parameters of the measurement model as "nuisance" parameters and use transformations of moments of the measurement data to eliminate them, analogous to the data transformations used to eliminate fixed effects with panel data. We develop additional, empirically grounded, restrictions on the measurement process that allow identification of more general production technologies, including those exhibiting Hicks neutral total factor productivity (TFP) dynamics and non-constant returns to scale. We use our identification results to develop a sequential estimation algorithm for the joint dynamic process of investment and skill development, correcting for the biases due to measurement error in skills and investment. Using data for the United States, we estimate the technology of skill formation, the process of parental investments in children, and the adult distribution of completed schooling and earnings, allowing the production technology and investment process to freely vary as the child ages. Our estimates of high TFP and increasing returns to scale at early ages indicate that investments are particularly productive at these ages. We find that the marginal productivity of early investments is substantially higher for children with lower existing skills, suggesting the optimal targeting of interventions to disadvantaged children. Our estimates of the dynamic process of investment and skill development allow us to estimate heterogeneous treatment effects of policy interventions. We show that even a modest transfer of family income to families at ages 5-6 would substantially increase children's skills, completed schooling, and adult earnings, with the effects largest for low income families.
    JEL: C38 J13
    Date: 2016–07
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:22442&r=eff

General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.