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This paper formulates and estimates multistage production functions for children's cognitive and noncognitive skills. Skills are determined by parental environments and investments at different stages of childhood. We estimate the elasticity of substitution between investments in one period and stocks of skills in that period to assess the benefits of early investment in children compared to later remediation. We establish nonparametric identification of a general class of production technologies based on nonlinear factor models with endogenous inputs. A by-product of our approach is a framework for evaluating childhood and schooling interventions that does not rely on arbitrarily scaled test scores as outputs and recognizes the differential effects of the same bundle of skills in different tasks. Using the estimated technology, we determine optimal targeting of interventions to children with different parental and personal birth endowments. Substitutability decreases in later stages of the life cycle in the production of cognitive skills. It is roughly constant across stages of the life cycle in the production of noncognitive skills. This finding has important implications for the design of policies that target the disadvantaged. For most configurations of disadvantage it is optimal to invest relatively more in the early stages of childhood than in later stages.

This paper summarises the literature on the estimation of production functions governing the process of skill formation. This literature focuses on attacking three problems. The first is the endogeneity of measures of investments. The second is the measurement error in skills and investments that are widely used in the literature. Endogeneity and measurement error produce, in general, inconsistent estimates. The third problem is the lack of a metric for tests designed to measure skills. The fact that scores have no cardinal meaning implies that the coefficients of the production function have no economic meaning. We show that anchoring test scores on outcomes that have a natural metric produces estimates that are economically interpretable.

A major econometric issue in estimating production parameters and technical efficiency is the possibility that some forces influencing production are only observed by the firm and not by the econometrician. Not only can this misspecification lead to a biased inference on the output elasticity of inputs, but it also provides a faulty measure of technical efficiency. We extend the Levinsohn and Petrin (2003) approach and provide an estimation algorithm to overcome the problem of endogenous input choice in stochastic production frontier estimation by generating consistent estimates of production parameters and technical efficiency. We apply the proposed method to a plant-level panel dataset from the Colombian food manufacturing sector for the period 1982–1998. This dataset provides the value of output and prices charged for each product, expenditures, and prices paid for each material used, energy consumption in kilowatt per hour and energy prices, number of workers and payroll, and book values of capital stock. Empirical results find that the traditional stochastic production frontier tends to underestimate the output elasticity of capital and firm-level technical efficiency. The evidence in this research suggests that addressing the endogeneity issue matters in stochastic production frontier analysis.

Intraplatform competition has received scant attention in prior studies, which predominantly study interplatform competition. We develop a middle-range theory of how complementarity between input control and a platform extension’s modularization—by inducing evolution—influences its performance in a platform market. Primary and archival data spanning five years from 342 Firefox extensions show that such complementarity fosters performance by accelerating an extension’s perpetual evolution.

The objective of this article is to examine the association between agricultural subsidies and dairy farm technical efficiency in the European Union, and in so doing we make novel contributions to the literature.We include in the analysis nine diverse western European Union (EU) countries over an 18-year period (1990–2007) encompassing the various Common Agricultural Policy (CAP) reforms enacted since the inception of the EU. Further, we account for input endogeneity using an original method of moments estimator. Our results show that the effect of subsidies on technical efficiency may be positive, null, or negative, depending on the country. The analysis reveals that the introduction of decoupling with the 2003 CAP reform weakens the effect that subsidies have on technical efficiency.

This article uses a double-hurdle model with panel data from Malawi to investigate how fertilizer subsidies affect farmer demand for commercial fertilizer. The article controls for potential endogeneity caused by the nonrandom targeting of fertilizer subsidy recipients. Results show that on average 1 additional kilogram of subsidized fertilizer crowds out 0.22 kg of commercial fertilizer, but crowding out ranges from 0.18 among the poorest farmers to 0.30 among relatively nonpoor farmers. This indicates that targeting fertilizer subsidies to the rural poor is likely to maximize the contribution of the subsidy program to total fertilizer use.

The importance of credit in agriculture and technology adoption is well researched, but little is known about its impact on the intensity of climate adaptation strategies (CAS) utilization. To contribute to the literature on climate change, the study examines the impact of credit status on the intensity of CAS utilization with its treatment effects. Unlike previous studies that investigated CAS as binary decisions or multi-class models, the study changed the narrative by measuring the number of CAS adopted and utilized by crop farmers. Farm-level data were collected from 150 crop farmers in Southwest Nigeria using a well-designed questionnaire. Descriptive statistics and the endogenous treatment Poisson regression (ETPR) model were used for the data analysis. The results revealed that credit status positively and significantly impacts the intensity of CAS utilization. Other farm-level factors that jointly impacted CAS utilization were education, experience, age, income, extension contacts and farm size. Likewise, the credit status co-joints with climate variables, such as access to climate information, perceived rainfall and temperature, to impact the intensity of CAS utilization in the area. Based on the treatment effects estimates, an average crop farmer will utilize 1.986 times CAS more when he is not being credit constrained, while the average crop farmer in the treated group will utilize 1.757 times CAS more than it would if s/he is credit constrained. Thus, the policy should focus on revamping credit institutions that prioritize requisite adaptation strategy resources.

Agricultural extension is an important policy instrument utilized to diffuse knowledge and increase profitability among farmers. However, analyses on impact are subject to endogeneity concerns, causing multiple biases. Failure to combat endogeneity can lead to false inferences on impact. This article addresses this issue by applying an instrumental variable approach with distance to local advisory office and a policy change chosen as instruments for extension participation. The results show that participation significantly increased farm income and that OLS estimates underestimated the impact. Therefore, a superior estimate of impact is achieved which can be leveraged to better support accurate policy making.

The paper provides findings on the technical efficiency of the European dairy processing industry, which is one of the most important subsectors of the food processing industry in the European Union (EU). The ability to efficiently use inputs in the production of outputs is a prerequisite for the sustainability and competitiveness of the agri-food sector as well as for food security. Thus, the aim of this paper is to provide a robust estimate of technical efficiency by employing new advances in productivity and efficiency analysis, and to investigate the efficiency of input use in 10 selected European countries. The analysis is based on two-stage stochastic frontier modelling incorporating country-specific input distance function (IDF) estimates and a meta-frontier input distance function estimate, both in specification of the four-component model, which currently represents the most advanced approach to technical efficiency analysis. To provide a robust estimate of these models, the paper employs methods that control for the potential endogeneity of netputs in the multi-step estimation procedure. The results, based on the Amadeus dataset, reveal that companies manufacturing dairy products greatly exploited their production possibilities in 2006–2018. The dairy processing industry in the analysed countries cannot generally be characterized by a considerable waste of resources. The potential cost reduction is estimated at 4–8%, evaluated on the country samples mean. The overall technical inefficiency (OTE) is mainly a result of short-term shocks and unsystematic failures. However, the meta-frontier estimates also reveal a certain degree of systematic failure, e.g., permanent managerial failures and structural problems in European dairy processing industry.

Multi-input multi-output production technologies can be represented using distance functions. Econometric estimation of these functions typically involves factoring out one of the outputs or inputs and estimating the resulting equation using maximum likelihood methods. A problem with this approach is that the outputs or inputs that are not factored out may be correlated with the composite error term. Fernandez et al. (J Econ 98:47-79, 2000) show how to solve this so-called 'endogeneity problem' using Bayesian methods. In this paper I use the approach to estimate an output distance function and an associated index of total factor productivity (TFP) change. The TFP index is a new index that satisfies most, if not all, economically-relevant axioms from index number theory. It can also be exhaustively decomposed into a measure of technical change and various measures of efficiency change. I illustrate the methodology using state-level data on U.S. agricultural input and output quantities (no prices are needed). Results are summarized in terms of the characteristics (e.g., means) of estimated probability density functions for measures of TFP change, technical change and efficiency change.