Reducing poverty in developing countries has been a longstanding and central concernof development economics. Over the past two decades, there has been a noticeable shift inthe approach taken by development economists to address this question. Researchers haveincreasingly focused their efforts on randomized controlled trials — an experimentalapproach commonly used in medical research — to determine the effectiveness of anti-poverty programs and interventions. his shift was highlighted by the 2019 Nobel Prize inEconomics awarded to Abhijit Banerjee, Esther Duflo, and Michael Kremer[42], whichrecognized their work for breaking down the issue of fighting global poverty into "smaller,more manageable, questions – for example, the most effective interventions for improvingeducational outcomes or child health." One question that remains, though, is how muchoverall reduction in the poverty rate one can expect from projects, programs, or policyinterventions that raise the well-being of those in absolute poverty at a given level of income,versus how much poverty reduction comes from broad-based economic growth.
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CHAPTER THREE: Economic situation and poverty analysis in China and Gabon......................13
3.1The economic situation in China and Gabon....................... 14
3.1.1 The economic situation in China...................................14
3.2The economic situation in Gabon................................ 16
CHAPTER FOUR: Poverty reduction in China and Gabon............................28
4.1 Poverty reduction in China..................................29
4.1.1 Governance in China..................................29
4.1.2 Anti-poverty policies and anti-corruption campaign in China......................................... 30
CHAPTER FIVE: Material and Methods................................45
5.1Sampling and data collection........................... 45
5.2Causality principle............................. 46
CHAPTER SIX: RESULTS AND DISCUSSION
6.1 Result
6.1.1 Measurement model
Confirmatory factor analysis (CFA) was used to check the validity of the measurements.The results are shown in Table 7. The measurement's trustworthiness was assessed. All ofthe composite reliability values and the Cronbach value were above the 0.7 thresholds,indicating high reliability [73]. The measuring model assessed the data fit (Table 7).
Table 7 Reliability and validity analyses
The majority of the results presented in this paper are well-known. As a result, financialgrowth in Gabon is closely linked to governance change (β=0.25, p<0.01), and H1a isacknowledged. Governance reform has a major and optimistic effect on China's financialgrowth (β=0.39, p<0.01), so H1b is embraced. However, the results indicate that Gabon'sfinancial growth (β=0.04, p<0.31) had no substantial impact on poverty reduction, so H2 wasrejected.H3 has been acknowledged because of the impact of financial growth in China((β=0.17, p<0.01) has a clear and positive effect on poverty reduction (Table 7.1).
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CHAPTER SEVEN: Conclusion and recommendation
7.1 Conclusion
This research compared poverty levels in China and Gabon. To do so, the study lookedat each other's poverty levels using China and Gabon's respective poverty rates, then arguedthat poverty in Gabon was not only systemic (linked to a lack of institutions orinfrastructure), but also political (linked to inadequate government policies, etc.). However,poverty in China is linked to the inability of