Main Article Content
Abstract
Fluctuations in world crude oil prices significantly impact oil-importing countries like Indonesia. These fluctuations affect multiple sectors, including the import of consumer goods, which is vital for the domestic economy. In Indonesia, consumer goods are crucial for economic stability. Thus, understanding how oil price fluctuations influence imports is essential for policymaking. This study investigates the relationship between world crude oil price fluctuations and the import value of consumer goods in Indonesia over an extended period. A quantitative approach was used, treating world crude oil prices as the independent variable and the import value of consumer goods as the dependent variable. Linear regression analysis, supported by descriptive statistical methods, was employed to assess this relationship. The results indicate that world crude oil prices have a significant effect on the import value of consumer goods, with data showing near-normal distribution and low skewness and kurtosis, validating the model. However, positive autocorrelation in the residuals suggests the need for further analysis to ensure the reliability of the model. These findings offer important insights for policymakers on managing the economic impact of oil price volatility on Indonesia’s domestic market. Future research could explore additional factors, such as inflation or trade policy, that may influence this relationship, contributing to more effective economic strategies.
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Article Details
References
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- Bistacchi, A., Mittempergher, S., Martinelli, M., & Storti, F. (2020). On a new robust workflow for the statistical and spatial analysis of fracture data collected with scanlines (or the importance of stationarity). Solid Earth, 11(6), 2535–2547. https://doi.org/10.5194/se-11-2535-2020
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- Chelli, A., & Patzold, M. (2011). A non-stationary mimo vehicle-to-vehicle channel model derived from the geometrical t-junction model.
- Dahlhaus, R., Richter, S., & Wu, W. (2019). Towards a general theory for nonlinear locally stationary processes. Bernoulli, 25(2). https://doi.org/10.3150/17-bej1011
- Darmawan, I., Siregar, H., Hakim, D., & Manurung, A. (2020). The effect of crude oil price shocks on Indonesia stock market performance. Jurnal Organisasi Dan Manajemen, 16(1), 11–23. https://doi.org/10.33830/jom.v16i1.785.2020
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- Gao, X., & Fang, Y. (2016). Penalized weighted least squares for outlier detection and robust regression.
- Ghosh, H., & Paul, R. (2010). Wavelet frequency domain approach for statistical modeling of rainfall time-series data. Journal of Statistical Theory and Practice, 4(4), 813–825. https://doi.org/10.1080/15598608.2010.10412020
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- Hesikumalasari, H., Budiantara, I., Ratnasari, V., & Nisa, K. (2022). Estimation of semiparametric regression curve with mixed estimator of multivariable linear truncated spline and multivariable kernel. Media Statistika, 15(1), 12–23. https://doi.org/10.14710/medstat.15.1.12-23
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- Iwueze, I., Nwogu, E., Ohakwe, J., & Ajaraogu, J. (2011). Uses of the Buys-Ballot table in time series analysis. Applied Mathematics, 2(5), 633–645. https://doi.org/10.4236/am.2011.25084
- Kim, S., Park, H., Jung, H., Lee, J., & Lim, K. (2021). Estimation of health-related physical fitness using multiple linear regression in Korean adults: National Fitness Award 2015–2019. Frontiers in Physiology, 12. https://doi.org/10.3389/fphys.2021.668055
- Koo, B., & Linton, O. (2012). Estimation of semiparametric locally stationary diffusion models. Journal of Econometrics, 170(1), 210–233. https://doi.org/10.1016/j.jeconom.2012.05.003
- Kuntz, J., Ottobre, M., Stan, G., & Barahona, M. (2016). Bounding stationary averages of polynomial diffusions via semidefinite programming. SIAM Journal on Scientific Computing, 38(6), A3891–A3920. https://doi.org/10.1137/16m107801x
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- Lieshout, v. (2011). A J–function for inhomogeneous point processes. Statistica Neerlandica, 65(2), 183–201. https://doi.org/10.1111/j.1467-9574.2011.00482.x
- Liu, Z., Ren, L., Xiao, C., Zhang, K., & Demian, P. (2022). Virtual reality aided therapy towards health 4.0: a two-decade bibliometric analysis. International Journal of Environmental Research and Public Health, 19(3), 1525. https://doi.org/10.3390/ijerph19031525
- Makala, D., & Li, Z. (2019). Economic forecasting with deep learning: crude oil. Matter International Journal of Science and Technology, 5(2), 213–228. https://doi.org/10.20319/mijst.2019.52.213228
- Mishra, P., Pandey, C., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103/aca.aca_157_18
- Nandha, M., & Faff, R. (2008). Does oil move equity prices? a global view. Energy Economics, 30(3), 986–997. https://doi.org/10.1016/j.eneco.2007.09.003
- Nasir, J., Aamir, M., Haq, Z., Khan, S., Amin, M., & Naeem, M. (2023). A new approach for forecasting crude oil prices based on stochastic and deterministic influences of LMD using ARIMA and LSTM models. IEEE Access, 11, 14322–14339. https://doi.org/10.1109/access.2023.3243232
- Novković, N., Vukelić, N., Šarac, V., & Nikolić, S. (2022). State and tendencies of production characteristics of wheat and maize in Serbia. Journal on Processing and Energy in Agriculture, 26(2), 68–70. https://doi.org/10.5937/jpea26-37904
- Östlund, U., Kidd, L., Wengström, Y., & Rowa-Dewar, N. (2011). Combining qualitative and quantitative research within mixed method research designs: a methodological review. International Journal of Nursing Studies, 48(3), 369–383. https://doi.org/10.1016/j.ijnurstu.2010.10.005
- Paparoditis, E. (2009). Testing temporal constancy of the spectral structure of a time series. Bernoulli, 15(4). https://doi.org/10.3150/08-bej179
- Prabheesh, K., & Laila, N. (2020). Asymmetric effect of crude oil and palm oil prices on economic growth: evidence from Indonesia. Buletin Ekonomi Moneter Dan Perbankan, 23(2), 253–268. https://doi.org/10.21098/bemp.v23i1.1304
- Priwiningsih, V., & Abidin, A. (2022). Literature study of cooking oil scarcity and the increase of cooking oil prices in Indonesia. Proceedings of International Conference on Economics Business and Government Challenges, 5(1), 87–92. https://doi.org/10.33005/ic-ebgc.v1i1.14
- Pusparum, M., Kurnia, A., & Alamudi, A. (2017). Winsor approach in regression analysis with outlier. Applied Mathematical Sciences, 11, 2031–2046. https://doi.org/10.12988/ams.2017.76214
- Richardson, D., MacLehose, R., Langholz, B., & Cole, S. (2011). Hierarchical latency models for dose-time-response associations. American Journal of Epidemiology, 173(6), 695–702. https://doi.org/10.1093/aje/kwq387
- Steinitz, G., Piatibratova, O., & Barbosa, S. (2007). Radon daily signals in the Elat granite, southern Arava, Israel. Journal of Geophysical Research: Atmospheres, 112(B10). https://doi.org/10.1029/2006jb004817
- Suherman, S., Syaifuddin, S., & Faris, S. (2022). The effect of leadership style and career development on employee performance at CV Setia Kawan Medan. International Journal of Science Technology & Management, 3(5), 1460–1464. https://doi.org/10.46729/ijstm.v3i5.588
- Suryani, D., Fadhilla, M., & Labellapansa, A. (2022). Indonesian crude oil price (ICP) prediction using multiple linear regression algorithm. Jurnal Resti (Rekayasa Sistem Dan Teknologi Informasi), 6(6), 1057–1063. https://doi.org/10.29207/resti.v6i6.4590
- Syah, H., Irmansyah, J., Hulfian, L., & Lubis, M. (2022). Hybrid learning space as an alternative for physical education learning post COVID-19 pandemic. International Journal of Human Movement and Sports Sciences, 10(5), 1047–1059. https://doi.org/10.13189/saj.2022.100523
- Vandyck, T., Kitous, A., Saveyn, B., Keramidas, K., Santos, L., & Wójtowicz, K. (2018). Economic exposure to oil price shocks and the fragility of oil-exporting countries. Energies, 11(4), 827. https://doi.org/10.3390/en11040827
- Velicer, W., & Fava, J. (2003). Time series analysis. In Encyclopedia of Statistical Sciences (pp. 581–606). https://doi.org/10.1002/0471264385.wei0223
- Wen, F., Ming, F., Zhang, Y., & Yang, C. (2018). Crude oil price shocks, monetary policy, and China’s economy. International Journal of Finance & Economics, 24(2), 812–827. https://doi.org/10.1002/ijfe.1692
- Williamson, J., Lin, H., & Lyles, R. (2023). A censored quantile regression approach for relative survival analysis: relative survival quantile regression. Biometrical Journal, 65(5). https://doi.org/10.1002/bimj.202200127
References
Adhikari, G. (2022). Interpreting the basic results of multiple linear regression. Scholars Journal, 22–37.
Arintoko, A. (2023). Asymmetric effects of world energy prices on inflation in Indonesia. International Journal of Energy Economics and Policy, 13(6), 185–193. https://doi.org/10.32479/ijeep.14731
Ayadi, O. (2005). Oil price fluctuations and the Nigerian economy. Opec Review, 29(3), 199–217. https://doi.org/10.1111/j.0277-0180.2005.00151.x
Berentzen, T., Ängquist, L., Kotronen, A., Borra, R., Yki-Järvinen, H., Iozzo, P., & Jakobsen, M. (2012). Waist circumference adjusted for body mass index and intra-abdominal fat mass. Plos One, 7(2), e32213. https://doi.org/10.1371/journal.pone.0032213
Bistacchi, A., Mittempergher, S., Martinelli, M., & Storti, F. (2020). On a new robust workflow for the statistical and spatial analysis of fracture data collected with scanlines (or the importance of stationarity). Solid Earth, 11(6), 2535–2547. https://doi.org/10.5194/se-11-2535-2020
Charlot, F., & Rachdi, M. (2008). On the statistical properties of a stationary process sampled by a stationary point process. Statistics & Probability Letters, 78(4), 456–462. https://doi.org/10.1016/j.spl.2007.07.019
Chelli, A., & Patzold, M. (2011). A non-stationary mimo vehicle-to-vehicle channel model derived from the geometrical t-junction model.
Dahlhaus, R., Richter, S., & Wu, W. (2019). Towards a general theory for nonlinear locally stationary processes. Bernoulli, 25(2). https://doi.org/10.3150/17-bej1011
Darmawan, I., Siregar, H., Hakim, D., & Manurung, A. (2020). The effect of crude oil price shocks on Indonesia stock market performance. Jurnal Organisasi Dan Manajemen, 16(1), 11–23. https://doi.org/10.33830/jom.v16i1.785.2020
Destiarni, R., & Jamil, A. (2021). Price integration analysis of crude oil and vegetable oils. Habitat, 32(2), 82–92. https://doi.org/10.21776/ub.habitat.2021.032.2.10
Dette, H., Preuß, P., & Vetter, M. (2011). A measure of stationarity in locally stationary processes with applications to testing. Journal of the American Statistical Association, 106(495), 1113–1124. https://doi.org/10.1198/jasa.2011.tm10811
Firmansyah, M., Boedirochminarni, A., Riyanto, W., & Tsalasa, A. (2024). Do cashless transactions and credit distribution affect inflation in Indonesia? Ecoplan, 7(2), 144–153. https://doi.org/10.20527/ecoplan.v7i2.728
Gao, X., & Fang, Y. (2016). Penalized weighted least squares for outlier detection and robust regression.
Ghosh, H., & Paul, R. (2010). Wavelet frequency domain approach for statistical modeling of rainfall time-series data. Journal of Statistical Theory and Practice, 4(4), 813–825. https://doi.org/10.1080/15598608.2010.10412020
Guo, H., & Kliesen, K. (2005). Oil price volatility and U.S. macroeconomic activity. Review of Economic Dynamics, 87(6). https://doi.org/10.20955/r.87.669-84
Hayashi, Y., & Zhang, N. (2015). Evaluation of measurement precision from stationary baseline noise in instrumental analyses. Analytical Sciences, 31(12), 1219–1224. https://doi.org/10.2116/analsci.31.1219
Hesikumalasari, H., Budiantara, I., Ratnasari, V., & Nisa, K. (2022). Estimation of semiparametric regression curve with mixed estimator of multivariable linear truncated spline and multivariable kernel. Media Statistika, 15(1), 12–23. https://doi.org/10.14710/medstat.15.1.12-23
Hu, S., Xi, Z., McGowin, G., Sukthankar, G., Fiore, S., & Oden, K. (2021). Representing time series data in intelligent training systems. The International Flairs Conference Proceedings, 34(1). https://doi.org/10.32473/flairs.v34i1.128508
Hu, Z. (2021). Crude oil price prediction using CEEMDAN and LSTM-attention with news sentiment index. Oil & Gas Science and Technology – Revue D’IFP Energies Nouvelles, 76, 28. https://doi.org/10.2516/ogst/2021010
Ibrahim, M. (2008). Growth prospects of oil and gas abundant economies: the Nigerian experience (1970–2000). Journal of Economic Studies, 35(2), 170–190. https://doi.org/10.1108/01443580810870155
Imam, A. (2021). Untitled. Asian Journal of Mathematical Sciences, 4(4). https://doi.org/10.22377/ajms.v4i4.295
Iwueze, I., Nwogu, E., Ohakwe, J., & Ajaraogu, J. (2011). Uses of the Buys-Ballot table in time series analysis. Applied Mathematics, 2(5), 633–645. https://doi.org/10.4236/am.2011.25084
Kim, S., Park, H., Jung, H., Lee, J., & Lim, K. (2021). Estimation of health-related physical fitness using multiple linear regression in Korean adults: National Fitness Award 2015–2019. Frontiers in Physiology, 12. https://doi.org/10.3389/fphys.2021.668055
Koo, B., & Linton, O. (2012). Estimation of semiparametric locally stationary diffusion models. Journal of Econometrics, 170(1), 210–233. https://doi.org/10.1016/j.jeconom.2012.05.003
Kuntz, J., Ottobre, M., Stan, G., & Barahona, M. (2016). Bounding stationary averages of polynomial diffusions via semidefinite programming. SIAM Journal on Scientific Computing, 38(6), A3891–A3920. https://doi.org/10.1137/16m107801x
Li, J., Wang, X., & Wang, Z. (2023). Whether the air transport is going through the difficulties: evidence from dynamic changes in brent oil prices. BCP Business & Management, 38, 1386–1395. https://doi.org/10.54691/bcpbm.v38i.3901
Lieshout, v. (2011). A J–function for inhomogeneous point processes. Statistica Neerlandica, 65(2), 183–201. https://doi.org/10.1111/j.1467-9574.2011.00482.x
Liu, Z., Ren, L., Xiao, C., Zhang, K., & Demian, P. (2022). Virtual reality aided therapy towards health 4.0: a two-decade bibliometric analysis. International Journal of Environmental Research and Public Health, 19(3), 1525. https://doi.org/10.3390/ijerph19031525
Makala, D., & Li, Z. (2019). Economic forecasting with deep learning: crude oil. Matter International Journal of Science and Technology, 5(2), 213–228. https://doi.org/10.20319/mijst.2019.52.213228
Mishra, P., Pandey, C., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103/aca.aca_157_18
Nandha, M., & Faff, R. (2008). Does oil move equity prices? a global view. Energy Economics, 30(3), 986–997. https://doi.org/10.1016/j.eneco.2007.09.003
Nasir, J., Aamir, M., Haq, Z., Khan, S., Amin, M., & Naeem, M. (2023). A new approach for forecasting crude oil prices based on stochastic and deterministic influences of LMD using ARIMA and LSTM models. IEEE Access, 11, 14322–14339. https://doi.org/10.1109/access.2023.3243232
Novković, N., Vukelić, N., Šarac, V., & Nikolić, S. (2022). State and tendencies of production characteristics of wheat and maize in Serbia. Journal on Processing and Energy in Agriculture, 26(2), 68–70. https://doi.org/10.5937/jpea26-37904
Östlund, U., Kidd, L., Wengström, Y., & Rowa-Dewar, N. (2011). Combining qualitative and quantitative research within mixed method research designs: a methodological review. International Journal of Nursing Studies, 48(3), 369–383. https://doi.org/10.1016/j.ijnurstu.2010.10.005
Paparoditis, E. (2009). Testing temporal constancy of the spectral structure of a time series. Bernoulli, 15(4). https://doi.org/10.3150/08-bej179
Prabheesh, K., & Laila, N. (2020). Asymmetric effect of crude oil and palm oil prices on economic growth: evidence from Indonesia. Buletin Ekonomi Moneter Dan Perbankan, 23(2), 253–268. https://doi.org/10.21098/bemp.v23i1.1304
Priwiningsih, V., & Abidin, A. (2022). Literature study of cooking oil scarcity and the increase of cooking oil prices in Indonesia. Proceedings of International Conference on Economics Business and Government Challenges, 5(1), 87–92. https://doi.org/10.33005/ic-ebgc.v1i1.14
Pusparum, M., Kurnia, A., & Alamudi, A. (2017). Winsor approach in regression analysis with outlier. Applied Mathematical Sciences, 11, 2031–2046. https://doi.org/10.12988/ams.2017.76214
Richardson, D., MacLehose, R., Langholz, B., & Cole, S. (2011). Hierarchical latency models for dose-time-response associations. American Journal of Epidemiology, 173(6), 695–702. https://doi.org/10.1093/aje/kwq387
Steinitz, G., Piatibratova, O., & Barbosa, S. (2007). Radon daily signals in the Elat granite, southern Arava, Israel. Journal of Geophysical Research: Atmospheres, 112(B10). https://doi.org/10.1029/2006jb004817
Suherman, S., Syaifuddin, S., & Faris, S. (2022). The effect of leadership style and career development on employee performance at CV Setia Kawan Medan. International Journal of Science Technology & Management, 3(5), 1460–1464. https://doi.org/10.46729/ijstm.v3i5.588
Suryani, D., Fadhilla, M., & Labellapansa, A. (2022). Indonesian crude oil price (ICP) prediction using multiple linear regression algorithm. Jurnal Resti (Rekayasa Sistem Dan Teknologi Informasi), 6(6), 1057–1063. https://doi.org/10.29207/resti.v6i6.4590
Syah, H., Irmansyah, J., Hulfian, L., & Lubis, M. (2022). Hybrid learning space as an alternative for physical education learning post COVID-19 pandemic. International Journal of Human Movement and Sports Sciences, 10(5), 1047–1059. https://doi.org/10.13189/saj.2022.100523
Vandyck, T., Kitous, A., Saveyn, B., Keramidas, K., Santos, L., & Wójtowicz, K. (2018). Economic exposure to oil price shocks and the fragility of oil-exporting countries. Energies, 11(4), 827. https://doi.org/10.3390/en11040827
Velicer, W., & Fava, J. (2003). Time series analysis. In Encyclopedia of Statistical Sciences (pp. 581–606). https://doi.org/10.1002/0471264385.wei0223
Wen, F., Ming, F., Zhang, Y., & Yang, C. (2018). Crude oil price shocks, monetary policy, and China’s economy. International Journal of Finance & Economics, 24(2), 812–827. https://doi.org/10.1002/ijfe.1692
Williamson, J., Lin, H., & Lyles, R. (2023). A censored quantile regression approach for relative survival analysis: relative survival quantile regression. Biometrical Journal, 65(5). https://doi.org/10.1002/bimj.202200127