Dataset Information

A new look at the decomposition of agricultural productivity growth incorporating weather effects.

ABSTRACT: Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960-2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time.

SUBMITTER: Njuki E

PROVIDER: S-EPMC5821354 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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A new look at the decomposition of agricultural productivity growth incorporating weather effects.

Njuki Eric E Bravo-Ureta Boris E BE O'Donnell Christopher J CJ

PloS one 20180221 2

Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by ...[more]

PMID: 29466461

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Project description:BackgroundArthritis and joint pain are highly prevalent in agricultural (ag) workers. Many ag operations are sustained by a small number of workers, and the disability of even one worker thus contributes to economic hardship. This study investigated associations between joint health in Montana ag workers and economic well-being and work capacity.MethodsThis observational mixed-methods study utilized quantitative survey data and qualitative focus group data. 299 ranchers and farmers in 9 Montana counties completed either an online or paper survey that included participant demographics, joint symptoms, history of arthritis and arthritis type, financial status, work capacity, and the need to rely on others to complete one's work. The Western Ontario and McMaster Universities arthritis index (WOMAC) survey was completed by those with hip or knee pain. Data were entered into REDCap v8.9.2 for analysis with SAS 9.4, using logistic and linear regression models to detect associations between covariables and to calculate odds ratios and confidence intervals. Focus groups were held with ranchers in two Montana counties, discussing similar topics, and the themes expressed were identified.Results87.6% of survey respondents reported joint pain, 47.8% a diagnosis of arthritis, and 22.4% osteoarthritis (OA). A 10-point increase in WOMAC was significantly associated with lower work capacity (OR 2.00; 95% CI [1.58, 2.55], p < 0.01), worse financial condition (OR 1.23; 95% CI [1.01,1.48], p = 0.04), and increased reliance on others (OR 1.82; 95% CI [1.32, 2.55], p < 0.01). An arthritis diagnosis was associated with worsening work capacity (OR 4.66; 95% CI [2.71, 8.01], p < 0.01) and increased odds of relying on others (OR 3.23; 95% CI [1.56, 6.66], p < 0.01). A diagnosis of OA was significantly associated with decreased work capacity (OR 3.47; 95% CI [1.97, 6.11], p < 0.01). Unadjusted for age and BMI, we found a significant association between years spent working in agriculture and joint health, which became non-significant after adjusting for age and BMI. Focus group themes included decreased productivity with increased joint symptoms and a tendency for ranchers to avoid interaction with the health care system.ConclusionPoor joint health is associated with economic risk on Montana ranches and farms.

Dataset Information

A new look at the decomposition of agricultural productivity growth incorporating weather effects.

Publications

A new look at the decomposition of agricultural productivity growth incorporating weather effects.

Similar Datasets

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