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Data · dataset · 2025

Research Dataset on Rice Prices During the Food Scarcity in Post-War Taiwan (1945.8–1947.3)

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Description

This dataset focuses on the monthly average price of "premium Penglai rice" in the Taipei market during the early period of Taiwan's liberation (August 1945 March 1947), aiming to quantitatively reconstruct the fluctuation trajectory of rice prices during the food shortage period from 1945 to 1947, and provide a testable time series for studying post-war inflation, supply shocks, and policy failures. The data generation process is as follows: Firstly, the core source is the "Taiwan Price Statistics Monthly Report" compiled and printed by the Statistics Office of the Taiwan Provincial Governor's Office (original copy stored in the Shanghai Library, file number A541212001609239), which extracts the retail prices of Taipei, Taichung, and Kaohsiung in the "Penglai Rice Premium" column for 20 issues from August 1945 to March 1947 on a monthly basis; For the missing periods (1945-10, 1946-02, 1946-06), the original price matrix was formed by adding retail quotes from the same period's "Wen Hui Bao", "Taiwan Minbao", and Weng Jiaxi's "Reasons and Countermeasures for Taiwan's Early Post War Malignant Inflation".

Secondly, a dual character independent input+cross validation method is used to reduce transcription errors, and if the difference is greater than 5%, the original document will be retrieved; Subsequently, the unit of measurement was standardized based on the 1944 legal measurement of "500g ≈ 500g", and all records were converted to "Old Taiwan Dollars/500g". Thirdly, use IBM SPSS Statistics 27 to construct an exponential growth model: perform exponential regression in the first stage (1945-08-1946-05) and the fourth stage (1946-11-1947-03), respectively, to obtain the fitted monthly average price and 95% confidence interval; The residuals were found to follow a normal distribution (p>0.05) by Shapiro Wilk test, and the goodness of fit R ² was 0.969 and 0.955, indicating the reliability of the model.

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Fourth, calculate derivative indicators: total increase ∆, monthly average month on month α, doubling time, and include them in this dataset for future comparative research. 

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