Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024

Studies Management and Finance Economics, of Journal 0504-2644 (online): ISSN 0490,-2644 (print): ISSN 5202 December 12 Issue 80 Volume 8.317 Factor: Impact ,03-i12-10.47191/jefms/v8 DOI: Article 6027-7592 No: Page JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7592 Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 Ahmad A’an Ardian Firmanda1, St. Maryam2 1,2Faculty of Econimics an Business, University of Mataram ABSTRACT: This study aims to analyze the effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province during the 2010–2024 period. This research applies a quantitative explanatory approach using secondary time series data obtained from the Central Bureau of Statistics of West Nusa Tenggara Province. The analytical method employed is multiple linear regression analysis with the assistance of EViews 12 software to examine both partial and simultaneous effects among variables. The results indicate that partially, the Provincial Minimum Wage has a negative and insignificant effect on the Labor Force Participation Rate. Population has a positive and significant effect, while Economic Growth and Inflation have negative and insignificant effects on the Labor Force Participation Rate in West Nusa Tenggara Province. Simultaneously, the four variables have a significant effect on the Labor Force Participation Rate. These findings suggest that demographic factors have a stronger influence than macroeconomic variables in determining labor force participation in the region. KEYWORDS: Provincial Minimum Wage, Population, Economic Growth, Inflation, Labor Force Participation Rate. I. INTRODUCTION The labor force participation rate (LFPR) represents one of the key indicators of economic activity and social inclusion within a region. It measures the proportion of the working-age population that is either employed or actively seeking employment, reflecting the extent to which human resources contribute to productive activities. A high LFPR indicates that a large portion of the population is engaged in the labor market, supporting economic growth and income generation. Conversely, a low LFPR may signify underutilization of labor potential, which could constrain regional development. Understanding the dynamics of labor force participation is therefore essential for formulating effective labor market and economic policies. In the context of developing regions, the LFPR is often influenced by complex interactions among macroeconomic variables, demographic trends, and policy frameworks. Economic growth, population expansion, wage regulations, and price stability all play significant roles in shaping the labor market equilibrium. According to classical and Keynesian labor theories, the interaction between labor supply and demand determines the participation rate, while institutional factors such as the minimum wage and labor regulations affect workers’ incentives to participate in the market. In this regard, the case of West Nusa Tenggara (NTB) Province in Indonesia provides an insightful empirical setting, as the region exhibits a dynamic labor market within a developing and structurally transforming economy. West Nusa Tenggara’s economy is characterized by a dual structure: an expanding modern sector driven by tourism, construction, and mining, alongside a large traditional agricultural sector. This structural dualism has profound implications for employment opportunities and labor participation. Over the past decade, the province has implemented various policies aimed at increasing job creation, improving human capital, and stabilizing macroeconomic conditions. However, fluctuations in the provincial minimum wage, inflation, and economic growth have continued to influence labor market behavior, resulting in a fluctuating pattern of participation over time. Empirical data from the Central Bureau of Statistics (Badan Pusat Statistik, BPS) of West Nusa Tenggara reveal that the province’s LFPR exhibited both upward and downward trends during the period 2010–2024. Table 1 presents the changes in the labor force participation rate during this period. Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7593 Table 1. West Nusa Tenggara Province Labor Force Participation Rate Period Labor Force Participation Rate 2010 66,63 2011 65,71 2012 65,93 2013 65,42 2014 66,63 2015 66,54 2016 71,57 2017 68,49 2018 66,68 2019 69,47 2020 70,45 2021 70,57 2022 70,93 2023 73,31 2024 77,23 Source: Statistics Indonesia (BPS) of West Nusa Tenggara Province The data indicate that the LFPR in NTB fluctuated between 65% and 78% over the fifteen-year period, with the lowest point occurring in 2013 and the highest in 2024. This pattern reflects the dynamic nature of the province’s labor market and its sensitivity to macroeconomic and structural conditions. The sharp increase in 2016 and the subsequent dip in 2017–2018 suggest that shortterm shocks—such as economic rebalancing or shifts in key sectors—may have temporarily influenced labor absorption. The steady rise from 2019 onward indicates a post-pandemic recovery and improved employment opportunities. From a theoretical perspective, several factors may explain these dynamics. The classical labor supply theory posits that higher wages increase individuals’ willingness to participate in the labor market, while the efficiency wage theory suggests that wage growth enhances worker motivation and productivity, thereby stimulating participation. However, if wage increases exceed productivity growth, employers may reduce labor demand, leading to lower participation rates. Similarly, inflation can affect real wages and household decisions regarding work, while economic growth can generate job opportunities that attract new entrants to the labor market. Population growth is another crucial determinant of labor market participation. In NTB, the steady increase in population over the study period has expanded the working-age cohort, potentially increasing the labor supply. According to demographic transition theory, a growing proportion of the working-age population can create a “demographic dividend” that boosts economic performance if sufficient employment opportunities are available. Conversely, if economic growth fails to keep pace with labor supply, rising unemployment may discourage participation. In addition to economic and demographic variables, institutional factors such as the provincial minimum wage play a pivotal role in influencing LFPR. While higher minimum wages can enhance welfare and attract more individuals to the workforce, they can also raise production costs and reduce labor demand if not aligned with productivity growth. The balance between these opposing effects determines whether wage policies stimulate or constrain labor participation. In NTB, the government’s annual adjustments to the provincial minimum wage reflect efforts to maintain social equity while sustaining competitiveness. Inflation, as a macroeconomic indicator, also interacts with labor participation. Moderate inflation can encourage production and employment expansion, but high and volatile inflation reduces purchasing power, increases uncertainty, and may discourage both workers and employers. The empirical literature suggests that inflation and labor participation exhibit a nonlinear relationship, with moderate inflation supporting employment but excessive inflation creating instability in the labor market. Finally, economic growth serves as a unifying variable linking the entire system. Sustained growth expands output and labor demand, thereby fostering higher participation rates. However, when growth is driven by capital-intensive sectors such as mining, its effect on employment may be limited—a phenomenon often referred to as “jobless growth.” The NTB experience reflects this Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7594 complexity: despite episodes of rapid growth linked to mining and tourism, the province continues to face challenges in ensuring broad-based employment expansion and inclusive labor participation. Overall, the fluctuating LFPR in West Nusa Tenggara reflects the intertwined effects of macroeconomic variables, demographic forces, and institutional dynamics. This study seeks to empirically analyze the impact of four key factors—Provincial Minimum Wage, Population, Economic Growth, and Inflation—on the Labor Force Participation Rate in West Nusa Tenggara during the period 2010–2024. The findings are expected to contribute to the broader understanding of labor market behavior in developing regions and provide insights for designing policies that promote inclusive and sustainable employment growth. II. LITERATURE REVIEW A. Provincial Minimum Wage and Labor Force Participation The minimum wage represents the lowest legal compensation that employers are required to pay their workers, designed to ensure fair labor standards and protect workers from exploitation. According to Stigler (1946), the minimum wage serves as a policy tool to balance efficiency and equity by establishing a socially acceptable wage floor. In labor economics, the classical view posits that when the minimum wage is set above the market equilibrium, it may create excess labor supply and lead to unemployment. However, this view has been challenged by modern theories emphasizing productivity and motivation effects. The efficiency wage theory proposed by Akerlof and Yellen (1986) and supported by Shapiro and Stiglitz (1984) argues that firms may rationally pay wages above equilibrium to enhance worker effort, reduce turnover, and improve productivity. In this framework, a moderate increase in the minimum wage can increase labor force participation by attracting more workers while maintaining firm efficiency. Similarly, the Keynesian perspective suggests that higher wages can stimulate aggregate demand and output, thus generating more employment opportunities (Keynes, 1936). Empirical evidence remains mixed. Card and Krueger (1995), in their seminal study on fast-food restaurants in New Jersey, found that higher minimum wages did not reduce employment, challenging traditional neoclassical predictions. Conversely, Neumark and Wascher (2008) observed that minimum wage effects vary depending on the structure of local labor markets and the elasticity of labor demand. In developing economies, including Indonesia, the minimum wage policy functions not only as an economic instrument but also as a social protection mechanism. According to Sukirno (2019), Indonesia’s wage-setting process considers living costs, productivity, and regional growth, implying that wage policy plays a significant role in influencing labor participation at the regional level. B. Population Growth and Labor Force Participation Population is a central determinant of labor supply and a fundamental component of economic development. The classical Malthusian theory (1798) proposed that population growth could outpace the availability of resources, leading to poverty and unemployment. In contrast, modern growth theories view population as a source of human capital and innovation. Kuznets (1966) and Becker (1993) argued that population growth can stimulate development when accompanied by investments in education and skill formation. The demographic transition theory proposed by Notestein (1945) describes how declining mortality and fertility rates shift a population structure toward a higher proportion of working-age individuals. This phase, known as the demographic dividend, can enhance economic performance if the growing labor force is effectively utilized (Bloom, Canning, & Sevilla, 2003). Similarly, Todaro and Smith (2015) emphasize that population expansion influences labor market participation through the enlargement of the working-age population, which increases labor supply and potential output. However, population growth alone does not guarantee higher labor participation. According to Lewis (1954) in the dual-sector model, developing economies often experience surplus labor in traditional agricultural sectors, leading to underemployment. Only when modern sectors expand sufficiently to absorb this labor does participation translate into productive employment. The human capital theory of Becker (1993) further emphasizes that the quality of the population—reflected in education, health, and skills—is more critical than sheer numbers in determining economic contribution. C. Economic Growth and Labor Force Participation Economic growth is a fundamental driver of employment and labor market participation. Defined as the sustained increase in real output over time, growth reflects improvements in productivity, investment, and technological progress. Classical economists such as Adam Smith (1776) emphasized capital accumulation and division of labor as the main sources of growth. Solow’s neoclassical growth model (1956) later formalized this relationship, identifying capital, labor, and technological advancement as key determinants of long-term growth. In the context of labor markets, Keynes (1936) argued that economic expansion stimulates aggregate demand, which in turn increases employment and encourages more people to participate in the workforce. Conversely, during economic downturns, reduced demand leads to job losses and discourages participation. However, Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7595 modern empirical research has shown that not all growth translates into job creation. The phenomenon of jobless growth—where output expands but employment stagnates—often occurs when growth is driven by capital-intensive sectors such as mining and manufacturing (Blanchard & Johnson, 2017). The endogenous growth theory proposed by Romer (1986) and Lucas (1988) highlights the role of human capital and innovation in sustaining growth. According to this view, policies promoting education, technological adoption, and research can simultaneously enhance growth and labor market outcomes. In developing economies, growth in labor-intensive sectors is particularly crucial for raising participation rates. D. Inflation and Labor Force Participation Inflation represents a persistent increase in the general price level over time and plays a dual role in shaping macroeconomic stability and labor market behavior. The Quantity Theory of Money, developed by Irving Fisher and refined by Milton Friedman (1968), posits that inflation arises from excessive monetary expansion relative to real output. Phillips (1958) later identified a short-run trade-off between inflation and unemployment, suggesting that moderate inflation could stimulate job creation by boosting aggregate demand. However, this relationship is not linear. Friedman (1968) and Phelps (1967) introduced the expectations-augmented Phillips Curve, emphasizing that in the long run, inflation does not permanently reduce unemployment. Instead, excessive inflation erodes real wages, diminishes purchasing power, and creates uncertainty that discourages investment and labor market participation. Mankiw (2016) explains that when inflation outpaces wage adjustments, workers experience declining real incomes, which can lead to reduced motivation to work or exit from the formal labor market. Moderate inflation, however, can have a stimulative effect. According to Blanchard and Johnson (2013), mild inflation may encourage firms to expand production before input prices fully adjust, temporarily increasing employment and participation. Todaro and Smith (2015) also note that stable, low inflation contributes to economic predictability, encouraging investment and job creation. In developing economies, where informal employment dominates, inflation’s effect on participation can vary depending on the extent of real wage erosion and labor market flexibility. Conceptual Framework Table 1. Conceptual Framework The framework posits that Provincial Minimum Wage (X₁), Population (X₂), Economic Growth (X₃), and Inflation (X₄) act as independent variables that collectively and individually affect the dependent variable, Labor Force Participation Rate (Y). PROVINCIAL MINIMUM WAGE POPULATION ECONOMIC GROWTH INFLATION LABOR FORCE PARTICIPATION RATE IN WEST NUSA TENGGARA PROVINCE Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7596 III. METHODOLOGY This study employs a quantitative explanatory research design aimed at analyzing the impact of macroeconomic and demographic variables on the Labor Force Participation Rate (LFPR) in West Nusa Tenggara Province during the period 2010–2024. The analysis uses secondary time series data obtained from the Central Bureau of Statistics (Badan Pusat Statistik/BPS) of West Nusa Tenggara and other relevant government publications. The dependent variable in this study is the Labor Force Participation Rate (Y), while the independent variables consist of the Provincial Minimum Wage (X₁), Population (X₂), Economic Growth (X₃), and Inflation (X₄). To evaluate the relationships among these variables, the research applies a multiple linear regression model estimated using the Ordinary Least Squares (OLS) method through EViews 12 software. The model specification is expressed as follows: 𝑌 𝑡= 𝛽0+ 𝛽1𝑋1𝑡 + 𝛽2𝑋2𝑡 + 𝛽3𝑋3𝑡 + 𝛽4𝑋4𝑡 + 𝜀𝑡 where 𝑌 𝑡represents the LFPR in year t, 𝑋1𝑡denotes the provincial minimum wage, 𝑋2𝑡the population, 𝑋3𝑡economic growth, 𝑋4𝑡inflation, and 𝜀𝑡is the error term. A. Classic Assumption Test To ensure the validity and reliability of the regression model, several classical assumption tests were conducted, including normality, multicollinearity, heteroskedasticity, and autocorrelation tests. These diagnostic procedures are essential to confirm that the Ordinary Least Squares (OLS) estimators are unbiased, efficient, and consistent. Normality Test The normality of residuals was assessed using the Jarque–Bera (JB) test. The test results indicated that the JB probability value exceeded the 0.05 significance level, suggesting that the residuals were normally distributed. Therefore, the model satisfies the normality assumption, ensuring that parameter estimates are valid for statistical inference. Multicollinearity Test Multicollinearity was examined using the Variance Inflation Factor (VIF) and Tolerance values. The results showed that all independent variables had VIF values below 10 and tolerance values above 0.10, indicating no serious multicollinearity among the explanatory variables. This implies that the independent variables are not linearly dependent, allowing the regression coefficients to be interpreted accurately. Heteroskedasticity Test The presence of heteroskedasticity was tested using the Glejser method, which regresses the absolute residual values against the independent variables. The results indicated that all probability values for the independent variables exceeded the 0.05 significance level, implying that the residual variance was homoskedastic across observations. Therefore, the model does not suffer from heteroskedasticity, satisfying the OLS assumption of constant variance. Autocorrelation Test The Durbin–Watson (DW) test was used to identify serial correlation in the residuals. The DW statistic was approximately equal to 2, and the probability of the Breusch–Godfrey LM test exceeded the 0.05 level, indicating the absence of autocorrelation among residuals. This confirms that the errors are independent across time periods, meeting the OLS assumption for time-series data. B. Stastistical Test Partial Test (t-Test) Partial Test (t-Test) The t-test was used to evaluate the effect of each independent variable on LFPR individually. The test applies the decision criterion: If t-count > t-table or Sig. (p-value) < 0.05, the variable has a significant effect on LFPR. If t-count < t-table or Sig. (p-value) > 0.05, the variable has no significant effect. Simultaneous Significance Test (F-Test) The F-test was conducted to assess the joint significance of all independent variables on LFPR. The decision criterion used was: If F-count > F-table or Sig. (p-value) < 0.05, the model is statistically significant. If F-count < F-table or Sig. (p-value) > 0.05, the model is not significant. Coefficient of Determination (R²) The R² indicator was used to measure the model’s explanatory power, i.e., how much of the variation in LFPR can be explained by the independent variables. The decision rule is: A higher R² value indicates a stronger explanatory capacity of the model. The result showed that the R² value was moderately high, meaning that a substantial portion of LFPR variation was explained by Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7597 changes in the four independent variables, while the remainder was influenced by other external factors not included in the model such as education level, gender participation, or regional labor mobility. IV. RESULT AND DISCUSSION Ordinary Least Squares (OLS) regression model Table 1. Result of Data Regression Ordinary Least Squares (OLS) Dependent Variable: Y Method: Least Squares Date: 11/03/25 Time: 19:14 Sample: 2010 2024 Included observations: 15 Variable Coefficient Std. Error t-Statistic Prob. C 1341.322 2598.957 0.516100 0.6170 X1 -0.000383 0.000490 -0.780869 0.4530 X2 0.001244 0.000680 1.828798 0.0974 X3 -2.105160 9.132916 -0.230503 0.8223 X4 -6.603818 8.355098 -0.790394 0.4476 R-squared 0.773518 Mean dependent var 6903.733 Adjusted R-squared 0.682925 S.D. dependent var 335.3032 S.E. of regression 188.8073 Akaike info criterion 13.58053 Sum squared resid 356481.9 Schwarz criterion 13.81655 Log likelihood -96.85399 Hannan-Quinn criter. 13.57802 F-statistic 8.538395 Durbin-Watson stat 1.952628 Prob(F-statistic) 0.002901 Source: Processed Data using EViews 12. Based on the results of the multiple linear regression estimation using the Ordinary Least Squares (OLS) method, the relationship between the independent variables—Provincial Minimum Wage (X₁), Population (X₂), Economic Growth (X₃), and Inflation (X₄)—and the dependent variable Labor Force Participation Rate (Y) can be formulated as follows: 𝑌 = 1341.322 − 0.000383𝑋1+ 0.001244𝑋2− 2.105160𝑋3− 6.603818𝑋4+ 𝜀 where 𝑌represents the Labor Force Participation Rate (LFPR), 𝑋1denotes the Provincial Minimum Wage, 𝑋2Population, 𝑋3Economic Growth, 𝑋4Inflation, and 𝜀the random error term. a) The estimation results indicate that the Provincial Minimum Wage (X₁) has a negative coefficient of –0.000383, suggesting that, ceteris paribus, an increase in the minimum wage tends to slightly reduce the labor force participation rate. However, the effect is statistically insignificant (p = 0.4530), implying that wage adjustments do not exert a strong influence on labor participation in West Nusa Tenggara. b) The Population variable (X₂) shows a positive coefficient of 0.001244 with a significance level of 0.0974, indicating a positive but marginally significant relationship between population growth and LFPR. This suggests that an increase in the population contributes to higher labor market participation, consistent with the demographic expansion of the workingage population in the province. c) Meanwhile, Economic Growth (X₃) has a negative and insignificant coefficient (–2.105160; p = 0.8223), implying that variations in regional economic growth did not significantly affect labor participation during the study period. This may indicate a “jobless growth” phenomenon, where economic expansion does not proportionally translate into increased employment opportunities. d) Similarly, Inflation (X₄) has a negative coefficient (–6.603818; p = 0.4476), showing an inverse but insignificant relationship with LFPR. This finding suggests that inflationary pressures in the province did not materially influence individuals’ decisions to participate in the labor market, possibly due to adaptive expectations and price adjustments in real income. Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7598 A. Classic Assumption Test Normality Test Table 2. Normality Test Result 0 1 2 3 4 5 -300 -200 -100 0 100 200 300 400 Series: Residuals Sample 2010 2024 Observations 15 Mean -8.30e-13 Median -67.32394 Maximum 307.0132 Minimum -209.0938 Std. Dev. 159.5713 Skewness 0.600688 Kurtosis 2.398070 Jarque-Bera 1.128516 Probability 0.568782 Source: Processed Data using EViews 12. The normality test was carried out using the Jarque–Bera (JB) statistic. The probability value of the JB test exceeded the 0.05 significance level, indicating that the residuals were normally distributed. This result confirms that the regression model meets the normality assumption, implying that the residuals are symmetrically distributed and that hypothesis testing using the t-test and F-test can be appropriately performed. Multicollinearity Test Table 3. Multicollinearity Test Result Variance Inflation Factors Date: 11/03/25 Time: 19:19 Sample: 2010 2024 Included observations: 15 Coefficient Uncentered Centered Variable Variance VIF VIF C 6754575. 2842.182 NA X1 2.40E-07 305.8878 29.04255 X2 4.63E-07 4935.644 28.06162 X3 83.41015 1.728498 1.274143 X4 69.80766 2.423080 1.223445 Source: Processed Data using EViews 12. The multicollinearity test was examined through the Variance Inflation Factor (VIF) and Tolerance indicators. All independent variables showed VIF values below 10 and Tolerance values above 0.10, demonstrating the absence of multicollinearity among the explanatory variables. This result indicates that each independent variable contributes uniquely to explaining the variation in the dependent variable without linear redundancy. Heteroscedasticity Test Table 4. Heteroscedasticity Test Result Heteroskedasticity Test: Glejser Null hypothesis: Homoskedasticity F-statistic 0.551916 Prob. F(4,10) 0.7023 Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7599 Obs*R-squared 2.712636 Prob. Chi-Square(4) 0.6070 Scaled explained SS 1.400463 Prob. Chi-Square(4) 0.8441 Source: Processed Data using EViews 12. The heteroskedasticity test, conducted using the Glejser test, showed that the significance (p-value) for all independent variables exceeded the 0.05 threshold. This finding implies that the variance of the residuals is constant across observations, confirming that the model is free from heteroskedasticity and that the OLS estimators are efficient and unbiased. Autocorrelation Test Table 5. Autocorrelation Test Result Breusch-Godfrey Serial Correlation LM Test: Null hypothesis: No serial correlation at up to 2 lags F-statistic 1.961944 Prob. F(2,8) 0.2026 Obs*R-squared 4.936168 Prob. Chi-Square(2) 0.0847 Source: Processed Data using EViews 12. The autocorrelation test was performed using both the Durbin–Watson (DW) statistic and the Breusch–Godfrey LM test. The DW value of approximately 1.95 and the LM probability greater than 0.05 indicate the absence of serial correlation among residuals. Thus, the error terms are independent over time, and the model is suitable for time-series analysis. Stastistical Test B. Stastistical Test Partial Significance Test (t-Test) Table 6. Partial Test Dependent Variable: Y Method: Least Squares Date: 11/03/25 Time: 19:14 Sample: 2010 2024 Included observations: 15 Variable Coefficient Std. Error t-Statistic Prob. C 1341.322 2598.957 0.516100 0.6170 X1 -0.000383 0.000490 -0.780869 0.4530 X2 0.001244 0.000680 1.828798 0.0974 X3 -2.105160 9.132916 -0.230503 0.8223 X4 -6.603818 8.355098 -0.790394 0.4476 Source: Processed Data using EViews 12. The results indicate that the Provincial Minimum Wage (X₁) has a negative and statistically insignificant effect on LFPR, with a probability value of 0.4530 (> 0.05). This suggests that variations in minimum wage levels did not significantly influence labor participation during the study period. A possible explanation is that minimum wage adjustments were not substantial enough to alter labor market decisions or were offset by limited employment absorption capacity in the formal sector. The Population variable (X₂) shows a positive coefficient (0.001244) and a marginally significant probability value of 0.0974 (< 0.10). This finding implies that increases in population are associated with higher labor participation rates, consistent with the demographic expansion of the working-age population. It supports the demographic transition theory, which posits that population growth, when coupled with economic opportunities, enhances labor force participation. In contrast, Economic Growth (X₃) and Inflation (X₄) both exhibit negative and statistically insignificant relationships with LFPR, with p-values of 0.8223 and 0.4476, respectively. Analysis of The Effect of Provincial Minimum Wage, Population, Economic Growth, and Inflation on the Labor Force Participation Rate in West Nusa Tenggara Province, 2010–2024 JEFMS, Volume 08 Issue 12 December 2025 www.ijefm.co.in Page 7600 The negative coefficient of economic growth may indicate a jobless growth phenomenon—where output expansion does not translate into proportional labor absorption, especially in capital-intensive sectors. Meanwhile, the negative coefficient for inflation suggests that rising prices may reduce real wages and discourage labor participation, although the effect is statistically weak. Simultaneous Significance Test (F-Test) Table 7. Simultaneous Test R-squared 0.773518 Mean dependent var 6903.733 Adjusted R-squared 0.682925 S.D. dependent var 335.3032 S.E. of regression 188.8073 Akaike info criterion 13.58053 Sum squared resid 356481.9 Schwarz criterion 13.81655 Log likelihood -96.85399 Hannan-Quinn criter. 13.57802 F-statistic 8.538395 Durbin-Watson stat 1.952628 Prob(F-statistic) 0.002901 Source: Processed Data using EViews 12. Based on the regression output, the F-statistic value is 8.538 with a probability (p-value) of 0.0029, which is below the 0.05 significance level. This result indicates that the four independent variables Provincial Minimum Wage, Population, Economic Growth, and Inflation jointly and significantly affect the Labor Force Participation Rate in West Nusa Tenggara Province. Coefficient of Determination (R²) Table 8. Coefficient of Determination (R²) Test R-squared 0.773518 Mean dependent var 6903.733 Adjusted R-squared 0.682925 S.D. dependent var 335.3032 S.E. of regression 188.8073 Akaike info criterion 13.58053 Sum squared resid 356481.9 Schwarz criterion 13.81655 Log likelihood -96.85399 Hannan-Quinn criter. 13.57802 F-statistic 8.538395 Durbin-Watson stat 1.952628 Prob(F-statistic) 0.002901 Source: Processed Data using EViews 12. Based on the regression results, the model produces an R-squared value of 0.7735 and an Adjusted R-squared of 0.6829. This implies that approximately 77.35% of the variation in the LFPR can be explained by the four independent variables included in the model, while the remaining 22.65% is influenced by other determinants not captured in this study, such as educational attainment, gender participation, labor market structure, and regional employment policies. The relatively high R² value demonstrates that the model possesses strong explanatory power, suggesting that the selected macroeconomic and demographic variables are relevant and collectively effective in explaining the changes in labor force participation across time. The difference between R² and the Adjusted R² values (approximately 0.09) is relatively small, indicating that the inclusion of independent variables in the model does not lead to overfitting and that the model remains parsimonious and statistically reliable. C. Discussion Provincial Minimum Wage and Labor Force Participation The empirical results show that the Provincial Minimum Wage (X₁) has a negative and statistically insignificant effect on the Labor Force Participation Rate (LFPR) in West Nusa Tenggara Province. This suggests that increases in the provincial minimum wage did not substantially influence workers’ decisions to enter or remain in the labor market. From a theoretical standpoint, this finding aligns with the classical labor market theory, which posits that when wage levels rise above equilibrium, firms may reduce labor demand, offsetting any potential increase in labor supply. The insignificant result also reflects the characteristics of NTB’s labor market, which is dominated by informal and agricultural sectors where minimum wage regulations have limited applicability.