## 4 Regression Analysis
### Estimation Results
Next, we discuss the impact of GPP adoption on a municipality's measurement of its own green purchasing. Column (2) of Table 1 summarizes the estimation results for the measurement of green purchasing. This column shows that the APEs of the adoption of a GPP are positive and statistically significant for all items. Moreover, almost all of the APEs are larger than 20%. As shown in column (2) of Table 1, the highest APE of the implementation of GPP on a municipality's measurement of its own green purchasing rate is approximately 28% for office equipment and work gloves. The second highest APE, approximately 26%, is found for electronic devices. The third highest APE, roughly 25%, is found for office furniture. The fourth highest APE is approximately 23% for stationery, water heaters, and bedclothes. Imaging equipment and other fiber products have the fifth highest APE, which is approximately 22%. Mobile phones, home appliances, lighting equipment, and uniforms have an APE of approximately 21%. The APE is less than 20% for the remaining items. Among them, fire extinguishers have an APE of approximately 19%. Other public services have an APE of approximately 17%, while the APE is approximately 16% for AC units. Paper products, cars, other equipment, and public services have the lowest APEs among the 21 items at approximately 12%. These results are similar with the results for the implementation of some green purchasing. We find that GPP adoption has higher APE on items that have a large difference in the share of municipalities with measuring their own green purchasing rate by with and without GPP. Similarly, several items with relatively higher values in terms of this difference have lower APEs. One example is uniforms, which differ by 28% between municipalities with and without a GPP but for which the APE of a GPP is 20%. In our analysis, the APE of \(GPP_{i}\) indicates its impact on the probability of implementing green purchasing or of the municipality measuring its own green purchasing rate. Then, we can interpret our estimation results as expected differences in the share of municipalities that implement green purchasing or that measure their green purchasing rate according to whether the municipality has adopted a GPP after controlling for the effects of municipalities' size. We can observe that this expected difference in the share of municipalities that measure their green purchasing rate is higher than the difference without controlling for municipalities' size, while the opposite is true for the case of whether a municipality implements green purchasing. Our estimation results are different from those illustrated in Figures 5 and 6 in the previous section. Before controlling for the effects of the municipalities' size, it appears that the impact of GPP adoption is greater on the implementation of green purchasing than on whether a municipality measures its own green purchasing rate. Figures 5 and 6 indicate that the differences in the share of municipalities that implement green purchasing between those with and without a GPP is higher than the difference in whether they measure their own gre purchasing rate, except for stationery, other fiber products, mobile phones, and water heaters (for detailed information, see Table 1). Moreover, these differences are not particularly great, with a mean value of approximately 5%. In contrast, our estimation results, which take into account the size of the municipalities, provide the opposite results, showing that GPP adoption has a greater effect on whether a municipality measures its green purchasing rate. GPP adoption has a higher APE on the measurement of green purchasing rate than on the implementation of green purchasing except in the case of paper products. Moreover, the extent of the difference in the green purchasing rate between municipalities with and without a GPP becomes greater. As argued by [PERSON] et al. (2017), GPP adoption can promote green purchasing.