Assessing the role of Fintech, technological infrastructure, and macroeconomic stability on per capita spending as a pathway to economic growth in Jordan

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Type of the article: Research Article

Abstract
This study examined per capita spending as a key indicator of domestic-level economic activity and households’ financial involvement, both of which are essential to promoting inclusive and sustainable economic growth. The analysis focused on the case of Jordan, covering the period 1993–2023, to investigate the effect of three key determinants of per capita expenditure: First, Fintech solutions as a main facilitator of financial inclusion; second, digital tools as the main indicator of digital infrastructure development level; and finally, macroeconomic indicators that mainly affect economic growth. Therefore, the Fully Modified Least Squares (FMOLS) method was applied to the data to emphasize the dynamic relationship between the three determinants in driving per capita expenditure.
The regression results showed a level of spending that naturally exists, even without other determinants, with a coefficient of 4.6 due to the government’s grants and subsidies. Furthermore, they affirmed that higher disposable income through wages, as well as effective financial access through remittance transfer payments and account ownership, enhances individual consumption and financial inclusion. Additionally, despite the large volume of cards, the insignificant impact on PCE suggested that Fintech solutions heavily vary with the progress of technological infrastructure, such as the internet and ICT, combined with the need for financial literacy to avoid misuse of them. Additionally, the negative impact of inflation and the insignificant effect of GDP suggest that without stable economic indicators, such as consistent GDP growth, controlled inflation, and income equality, digital financial solutions may struggle to deliver sustainable benefits in sustaining economic growth.

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    • Figure 1. Per capita expenditure growth
    • Figure 2. Growth trends of sample factors
    • Figure 3. Data series stationarity
    • Table 1. Research metrics
    • Table 2. Summary of descriptive statistics
    • Table 3. Correlation matrix
    • Table 4. ADF test results
    • Table 5. ADF results
    • Table 6. FMOLS regression model results
    • Conceptualization
      Jamileh Ali Mustafa
    • Data curation
      Jamileh Ali Mustafa
    • Formal Analysis
      Jamileh Ali Mustafa
    • Funding acquisition
      Jamileh Ali Mustafa
    • Investigation
      Jamileh Ali Mustafa
    • Methodology
      Jamileh Ali Mustafa
    • Project administration
      Jamileh Ali Mustafa
    • Resources
      Jamileh Ali Mustafa
    • Software
      Jamileh Ali Mustafa
    • Supervision
      Jamileh Ali Mustafa
    • Validation
      Jamileh Ali Mustafa
    • Visualization
      Jamileh Ali Mustafa
    • Writing – original draft
      Jamileh Ali Mustafa
    • Writing – review & editing
      Jamileh Ali Mustafa