A replication of "the effect of the conservation reserve program on rural economies: Deriving a statistical verdict from a null finding" (American Journal of Agricultural Economics, 2019) - Jiarui Tian (Economics: The Open-Access, Open-Assessment Journal, 2023)
This study replicates the paper "Brown, J. P., Lambert, D. M., & Wojan, T. R. (2019). The effect of the conservation reserve program on rural economies: deriving a statistical verdict from a null finding. American Journal of Agricultural Economics , 101 (2), 528-540" and their procedure for calculating the so-called ex post power of statistical tests of significance for regression coefficients. There appears no generally accepted method for calculating ex post power, and Brown, Lambert, and Wojan (BLW) provided a bootstrapping method that can be applied after the parameter of interest is estimated. They recommend researchers to use this procedure to investigate whether a statistically insignificant finding is likely to be due to a low power property of the significance test. This study makes two main contributions. First, it verifies whether the data and code that BLW provided are reliable to reproduce their results. Second, it constructs Monte Carlo experiments to assess the performance of BLW's method. The results indicate that their method produces ex post power estimates that are relatively close to the true power values. Mean power estimates are generally unbiased, and 95% of the estimates lie within +/− 5% points of the true power. In conclusion, my replication provides further evidence of the reliability of BLW's method.
Keywords: 330; bootstrapping; ex post power; Monte Carlo experiments; replication; statistical insignificance