Abstract

This paper examines the contribution of the consumption share to GDP from 1970 to 2019 to assess how income groups contributed to the share's stability, as well as the factors influencing its path and policy implications. Because the dependent variable is expressed in percentages and is not normally distributed, the Beta regression finite mixed model is the best tool for detecting latent income groups. We used Robust standard error to ensure the stability of the consumption share (i.e. the average propensity to consume APC). The analytical tool predicts the discovery of three previously unknown income groups. The following three latent groups were identified by the group means following the analysis: 0.82, 0.87, and 0.90 represent low-, medium-, and high-income groups, respectively, with probabilities of 0.27, 0.47, and 0.26 for their share contribution. The explanatory variables include employment, human capital (hc), total factor productivity at constant national prices (rtfpna), and the share of labor compensation in GDP. Each estimated parameter has a high significance and the expected sign. The policy implication is that the consumption share should be reduced in favor of the saving share by increasing employment opportunities and total factor productivity because it is relatively high. Furthermore, fighting inflation increases consumption while increasing spending on health care, education, and training stimulates economic growth by increasing the percentage saving ratio but at different levels.

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