Note(s): Ordinary Least Squares (OLS) regression model, t-statistics calculated based on the robust standard errors clustered at firm-level. Over-(under)investment in labor (OVER_LAB_it or UNDER_LAB_it) in firm i occurs when the ratio of the number of employees at the end of financial year t to the annual sales of firm i during year t is greater (lower) than the ratio of the total number of employees of all firms in the same industry sector in year t to the total annual sales for all firms in the same industry sector in year t. In the sub-sample of over-investment in labor, a higher (lower) positive number indicates a higher (lower) over-investment in labor. For ease of interpretation, the negative signs of the sub-sample for under-investment in labor are multiplied by −1 to obtain a positive number. Hence, a higher (lower) positive number indicates a higher (lower) under-investment in labor. The presence of PCBs_it is a dummy variable set to 1 if firm i in year t has politically-connected board member(s) and zero (0) otherwise. Columns 1 and 2 report the OVER_LAB regression coefficients and t-values in parentheses, columns 3–4 report the UNDER_LAB regression coefficients and t-values in parentheses. *, **, and *** indicate statistical significance at the 10, 5 and 1% levels, respectively (two-tailed). The definitions of variables are presented in  Appendix

Source(s): Table 8 by authors