Effects of Tourism on African Women Employment: Using Generalized Methods of Moments and Quantile Regression

Abstract

Abstract This study aims to fill an existing gap in the empirical literature by exploring the effect of tourism on women's employment in 42 African countries. This study uses panel generalized least square (GLS), two-step System generalized methods of moment (S-GMM), and quantile regression (QR) to evaluate the data from 1996 to 2020. Using the QR method, we could examine correlations between variables outside the data's mean. The two-step System GMM corrects biases by differencing variables. To verify that extreme observations do not influence our baseline results in our sample, we dropped five nations with the top and bottom numbers of visitor arrivals. There is evidence to suggest that tourism has a substantial impact on women's employment. Models are also run to see how tourism affects the employment of women in the agriculture, industrial, and service sectors. An increase in tourism is directly related to more women moving away from agriculture and into the manufacturing and service sectors. The key contributions of this study are to emphasize the importance of tourism for women's labor force, wage efficiency, and employment generation in that sector. The findings of this study have a valuable contribution to future research and policy discussions on the impact of the tourism industry on women's employment.