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      Small farms in North Carolina, United States: Analyzing farm and operator characteristics in the pursuit of economic resilience and sustainability

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          Abstract

          Ensuring the sustainability of small farms relies on understanding farm economics, a crucial yet often overlooked aspect. In North Carolina, many small farms are confronted with financial challenges and the risk of collapse. This study examines the factors that influence farm profitability while considering the intersectionality of race and gender. The findings reveal significant disparities in farm and operator characteristics. Specifically, first‐generation and retiree farmers exhibit a lower likelihood of profitability. Conversely, factors positively associated with profitability include owning larger farm acreage, engaging in commercial agricultural production, utilizing paid family labor, practicing full‐time farming, and being a non‐White minority farmer. To foster the sustainability of small farms, it is imperative to implement policies that support full‐time farming and incentivize the use of paid family labor. These measures can contribute to bolstering profitability and safeguarding the economic viability of small farms.

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          Mostly Harmless Econometrics

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            Multiple comparison analysis testing in ANOVA.

            The Analysis of Variance (ANOVA) test has long been an important tool for researchers conducting studies on multiple experimental groups and one or more control groups. However, ANOVA cannot provide detailed information on differences among the various study groups, or on complex combinations of study groups. To fully understand group differences in an ANOVA, researchers must conduct tests of the differences between particular pairs of experimental and control groups. Tests conducted on subsets of data tested previously in another analysis are called post hoc tests. A class of post hoc tests that provide this type of detailed information for ANOVA results are called "multiple comparison analysis" tests. The most commonly used multiple comparison analysis statistics include the following tests: Tukey, Newman-Keuls, Scheffee, Bonferroni and Dunnett. These statistical tools each have specific uses, advantages and disadvantages. Some are best used for testing theory while others are useful in generating new theory. Selection of the appropriate post hoc test will provide researchers with the most detailed information while limiting Type 1 errors due to alpha inflation.
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              Managing human resources in family firms: The problem of institutional overlap

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                Author and article information

                Journal
                Applied Economic Perspectives and Policy
                Applied Eco Perspectives Pol
                Wiley
                2040-5790
                2040-5804
                July 13 2023
                Affiliations
                [1 ] Department of Agribusiness and Applied Economics North Carolina A&T State University Greensboro North Carolina USA
                [2 ] Department of Economics North Carolina A&T State University Greensboro North Carolina USA
                [3 ] Department of Agricultural Economics Texas A&M University College Station Texas USA
                Article
                10.1002/aepp.13392
                5b70dde4-ea18-46fa-a59d-9e989ef171d2
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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