Ncial improvement, and power consumption on financial development in Indonesia over the period 1965018, this study applied the ARDL model to estimate the long-run and short-run connection amongst the variables. FMOLS, DOLS, and CCR have been applied to verify the robustness with the empirical findings from the ARDL model. The ARDL was selected because it is much more applicable inside the smaller sample and takes into account the error correction model. ARDL strategy supplies consistent and robust results since it makes it possible for describing the existence of an equilibrium partnership in each long-run and short-run dynamics without losing long-run info. The ARDL bounds test method can be applied irrespective of regardless of whether the underlying variables are integrated of order one I(1) or order zero I(0) by (Pesaran et al. 2001). To attain this, the augmented Dickey-Fuller (Dickey and Fuller 1979) and PhillipsNaftopidil Epigenetic Reader Domain Perron (PP) (Phillips and Perron 1988) unit root tests have been applied to test the stationarity of the variables. The existence of a cointegration connection amongst the series indicated the will need to proceed further to estimate the long-run and short-run relationship. As a result, the ARDL model bounds test for cointegration developed by Pesaran et al. (2001) was employed to decide the cointegration partnership. In addition, the ARDL model, FMOLS, DOLS, and CCR have been made use of to estimate the long-run partnership among the variables. BesidesEconomies 2021, 9,five ofthat, the ARDL error correction model (ECM) was employed to estimate the short-run relationship. The ARDL is applicable inside the case of a little sample, and it requires into consideration the ECM. Consequently ARDL will be the most proper model to work with within this study. ARDL approach provides consistent and robust results because it makes it possible for and describes the existence of an equilibrium connection with regards to the long-run and short-run dynamics with no losing the long-run information (Pesaran et al. 2001). The FMOLS, DOLS, and CCR have been utilized for robustness check. The unit root test is applied to confirm whether the mean and variance of the variables modify over time and to make sure regardless of whether the time-series data are stationary or nonstationary. The time-series data in some instances involve random attributes that influence the statistical inferences and lead to the estimate of a spurious model. To test for the unit root in the underlying variables, the null hypothesis that the variables are nonstationary was tested against the option. Despite that, the ARDL model for cointegration may be made use of irrespective of no matter if the variables are integrated of order I(0) or I(1). The unit root tests were applied to make sure that the variables are usually not integrated at the order I(two). The cumulative sum (CUSUM) of recursive residual and cumulative sum square (CUSUMSQ) of recursive residuals techniques created by (Brown et al. 1975) have been employed to detect the movement from the constancy of regression coefficients. To examine the relationship between economic growth along with the primary explanatory variables, this paper describes financial development as a function of industrialization, trade openness, economic improvement, and power consumption. Consequently, the uncomplicated financial model describing this connection can be presented inside the following functional type: GDPt = f ( MVAt , Tt , DCt , Mt , ECt) (1)exactly where GDP represents the real per capita gross domestic item, MV represents the A manufacturing value-added, T represents trade openness, DC represents domestic cred.