Febryana Dilla Setyaningrum
Universitas Muhammadiyah Semarang

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Analysis of Passenger Flight Distance as an Indicator of Economic Activity Ihsan Fathoni Amri; Suci Izzati; Rendi Andika Putra; Iva Aurellia Khalif; Febryana Dilla Setyaningrum; Isnaini Maulida; M. Al Haris
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv5i1pp111-124

Abstract

Understanding macroeconomic dynamics in the United States requires advanced forecasting techniques capable of capturing both seasonal structures and external shocks. This study investigates the relationship between passenger flight distance and the unemployment rate through the implementation of the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) model—an enhancement of the SARIMA framework. While SARIMA accounts for autoregressive, differencing, and moving average components with seasonal integration, SARIMAX further augments this structure by incorporating exogenous predictors, enhancing explanatory and predictive power. Monthly time series data from 2015 to 2024 were utilized, with flight distance as the endogenous variable and the unemployment rate as the exogenous regressor. The modeling procedure involved rigorous stationarity testing via the Augmented Dickey-Fuller (ADF) test, model selection using the Akaike Information Criterion (AIC), and residual diagnostics employing the Box–Ljung and Shapiro–Wilk tests. SARIMAX(0,1,0)(0,1,1)[12] + X emerged as the optimal specification, with all parameters statistically significant and a MAPE of 3.68%, denoting excellent forecast accuracy. Empirical findings reveal a significant and negative association between unemployment and air travel activity, emphasizing the role of labor market dynamics in shaping mobility trends. These results reinforce the utility of SARIMAX as a robust tool in macroeconomic forecasting and evidence-based policy formulation.
ECONOMETRIC MODELING OF REGIONAL GROSS DOMESTIC PRODUCT IN INDONESIA USING DYNAMIC PANEL DATA THROUGH THE ARELLANO-BOND GENERALIZED METHOD OF MOMENTS APPROACH Devi Mulya Astuti; Tantri Crystiana; Febryana Dilla Setyaningrum; Galuh Salwa Salsabila; M. Al Haris; Alwan Fadlurohman
RAGAM: Journal of Statistics & Its Application Vol 5, No 2 (2026): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v5i2.19859

Abstract

Economic growth is a primary indicator of regional development performance, as reflected by Gross Regional Domestic Product (GRDP). The dynamic nature of economic variables requires an analytical approach capable of capturing intertemporal relationships. This study examines changes in GRDP across 34 provinces in Indonesia during the period 2016-2023 using annual dynamic panel data estimated with the Arellano-Bond Generalized Method of Moments (GMM) estimator. The explanatory variables include investment, the open unemployment rate (TPT), the Human Development Index (HDI), population size, and the lagged dependent variable. Model specification is evaluated using the Sargan test and the Arellano-Bond serial correlation test. The results indicate that the estimated model satisfies the required diagnostic tests, suggesting that the estimator is appropriate for the analysis. Furthermore, the Wald test indicates that the regressors are jointly significant. Partial estimation results show that lagged GRDP, investment, the open unemployment rate (TPT), and the Human Development Index (HDI) significantly affect changes in GRDP, whereas population size does not have a statistically significant effect. Lagged GRDP and investment exert positive effects on changes in GRDP, while the open unemployment rate and the Human Development Index have significant negative effects.