پژوهش ها و چشم اندازهای اقتصادی

پژوهش ها و چشم اندازهای اقتصادی

پویایی‌های رابطۀ علّی بین مؤلفه‌های سیاست مالی: شواهدی نوین از رویکرد موجک

نویسندگان
1 دانشجوی دکتری، گروه اقتصاد، واحد یزد، دانشگاه آزاد اسلامی، یزد، ایران
2 استادیار گروه اقتصاد، واحد یزد، دانشگاه آزاد اسلامی، یزد، ایران
چکیده
بحران مالی جهانی در سال 2008 و همه‌گیری اخیر بیماری کرونا ویروس (COVID-19)، توجهات به موضوعات مرتبط با سیاست‌های مالی را برانگیخته است. ازآنجایی‌که سیاست مالی، نقش مهمی در کاهش هزینه‌های این بحران‌ها دارد، درک رابطه بین مؤلفه‌های سیاست مالی بسیار با اهمیت است و پیامدهای مهمی برای انتخاب سیاست‌های مالی در حوزه اقتصاد بخش عمومی دارد. این پژوهش با استفاده از داده‌های فصلی طی دوره 1397:4-1369:1، به بررسی پیوندهای علّی بین مؤلفه‌های سیاست مالی یعنی مخارج دولت (جاری و عمرانی) و درآمدهای دولت (مالیاتی و نفتی) در ایران پرداخته، و برای این منظور، ابتدا از آزمون علیت تودا-یاماموتو در حوزه زمانی برای بررسی رابطه علّی بین این متغیرها استفاده ‌شده است. علاوه بر این، با توجه به نمایش ویژگی‌های مختلف توسط متغیرها در دامنۀ فرکانس، یک تحلیل پویا از طریق رویکرد همبستگی و اختلاف‌فاز موجک برای بررسی این رابطه در حوزه زمان- فرکانس بین درآمدهای دولت و ترکیب مخارج صورت می‌گیرد. نتایج تحلیل موجک، نشان می‌دهد که ارتباط بین جفت‌های درآمد و مخارج دولت در تمام افق‌های زمانی، یکسان نیست و یک ناهمگونی قوی در روابط متقابل آشکارشده در طول زمان و در مقیاس‌های مختلف شناسایی می‌شود. به‌طورکلی نتایج پژوهش، اثرات علّی مختلف با تأیید فرضیه تسلط مخارج برای درآمدهای نفتی و فرضیه تسلط درآمد برای درآمدهای مالیاتی را در فرکانس‌های مختلف نشان می‌دهد.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Dynamics of Causality Relationships between Fiscal Policy Components: New Evidence from Wavelet Approach

نویسندگان English

Ahmad Pourmohammadi 1
zohre tabatabaienasab 2
Yhya Abtahi 2
Mohammad Ali Dehqantafti 2
1 Ph.D. Student of Economics, Yazd Branch, Islamic Azad University, Yazd, Iran
2 Assistant Professor of Economics, Yazd Branch, Islamic Azad University, Yazd, Iran
چکیده English

The 2008 global financial crisis and the new coronavirus disease (COVID-19) pandemic have attracted interest in the issue of fiscal policy. Since fiscal policy plays an important role in alleviating the costs of these crises, understanding the relationships between fiscal policy components is crucial and has important implications for choosing fiscal policies in the field of public economics. This study aims to examine the causal links between the fiscal policy components, i.e., government expenditures (current and development) and government revenues (tax and oil) in Iran, using quarterly data for the period of 1990:2-2019:1. For this purpose, first, we employ the time domain Toda-Yamamoto causality test to check the causal relationship among these variables. Then, due to the various characteristics of variables in the frequency bands, we implement a dynamic analysis through wavelet coherence approach and wavelet phase-difference in order to explore the joint time-frequency domain causal relationship between government revenues and expenditure categories. The results of the wavelet analysis show that the linkage between the government revenues and expenditures pairs is not the same across all time horizons and a strong heterogeneity in the revealed interrelationships is detected over time and across scales. Overall, the results reveal various causal effects and confirm the expenditure dominance hypothesis for oil revenue, and revenue dominance hypothesis for tax revenue at different frequencies.

کلیدواژه‌ها English

Fiscal policy
Government revenues and expenditures
Toda-Yamamoto causality
Wavelet coherence
Phase differences
ایزدخواستی، حجت (1397). اثرات پویای درآمدهای نفتی بر رفتار دولت در تخصیص هزینه‌های مصرفی عمومی و دفاعی. سیاست‌های راهبردی و کلان، 6(21): 50-25.
رضایی، عباسعلی و مهرآرا، محسن (1394). آزمون ارتباط علّی و هم‌انباشتگی میان درآمد و مخارج دولت: با لحاظ شکست ساختاری. مطالعات اقتصادی کاربردی ایران، 4(13):170-145
صمدی، علی حسین و زارع حقیقی، نغمه (1391). آزمون مجدد رابطه بین درآمد و مخارج دولت در ایران: متقارن یا نامتقارن؟. پژوهشنامه اقتصادی (رویکرد اسلامی-ایرانی)، 12(47): 152-123.
علیزاده، محمد و فتح الهی، الهام (۱۳۹۷). رابطه بین درآمد مالیاتی و مخارج دولت در ایران: رویکرد نوین آزمون باند و علیت تودا-یاماموتو. مجله اقتصادی (دوماهنامه بررسی مسائل و سیاستهای اقتصادی)، ۱۸(۷): ۴۷-۶۹.
کریمی، سعید و علی زاده، محمد (1386). بررسی رابطه علیت بین هزینه ها و درآمدهای دولت. نامه مفید، 13(60 (نامه اقتصادی)): 165-147.
کشتکاران، سلما؛ پیرایی، خسرو، ابراهیمی، مهرزاد و حقیقت، علی (۱۳۹۸). واکنش درآمد و مخارج دولت به عدم تعادل بودجه در ایران. پژوهشهای اقتصادی (رشد و توسعه پایدار)، ۱۹(۴): ۲۹-۵۰.
کمیجانی، اکبر و نظری، روح اله (۱۳۸۸). تأثیر اندازه دولت بر رشد اقتصادی در ایران. پژوهشهای اقتصادی (رشد و توسعه پایدار)، 9(۳): ۱-۲۸.
مداح، مجید؛ جیحون تبار، فوزیه و رضاپور، زهره (1393). توهّم مالی و تقاضا برای مخارج دولت در اقتصاد ایران. مجله تحقیقات اقتصادی، 49(4): 750-729.
موسوی جهرمی، یگانه و زائر، آیت (1387). بررسی اثر کسری بودجه دولت بر مصرف و سرمایه گذاری بخش خصوصی در ایران. پژوهشهای اقتصادی (رشد و توسعه پایدار)، 8(3): 1-19

Aguiar-Conraria, L., Azevedo, N., & Soares, M. J. (2008). Using wavelets to decompose the time–frequency effects of monetary policy. Physica A: Statistical mechanics and its Applications, 387(12): 2863-2878.
Aguiar-Conraria, L., & Joana Soares, M. (2011). Business cycle synchronization and the Euro: A wavelet analysis. Journal of Macroeconomics, 33(3): 477-489.
Aguiar‐Conraria, L., & Soares, M. J. (2014). The continuous wavelet transform: Moving beyond uni‐and bivariate analysis. Journal of Economic Surveys, 28(2): 344-375.
Asandului, M., Lupu, D., Maha, L. G., & Viorică, D. (2021). The asymmetric effects of fiscal policy on inflation and economic activity in post-communist European countries. Post-Communist Economies.
Athanasenas, A., Katrakilidis, C., & Trachanas, E. (2014). Government spending and revenues in the Greek economy: evidence from nonlinear cointegration. Empirica, 41(2): 365-376.
Baghestani, H., & McNown, R. (1994). Do revenues or expenditures respond to budgetary disequilibria?. Southern Economic Journal: 311-322.
Barro, Robert J. 1979. On the determination of the public debt. Journal of Political Economy, 87(5): 940-971.
Barunik, J., & Vacha, L. (2015). Realized wavelet-based estimation of integrated variance and jumps in the presence of noise. Quantitative Finance, 15(8): 1347-1364.
Bilgili, F., Koçak, E., Kuşkaya, S., & Bulut, Ü. (2020). Estimation of the co-movements between biofuel production and food prices: a wavelet-based analysis. Energy, 213, 118777.
Bravo, S., González-Chang, M., Dec, D., Valle, S., Wendroth, O., Zúñiga, F., & Dörner, J. (2020). Using wavelet analyses to identify temporal coherence in soil physical properties in a volcanic ash-derived soil. Agricultural and Forest Meteorology, 285, 107909.
Buchanan, J. M., & Wagner, R. E. (1978). Dialogues concerning fiscal religion. Journal of Monetary economics, 4(3): 627-636.
Buyukbasaran, T., Cebi, C., & Yılmaz, E. (2020). Interaction of monetary and fiscal policies in Turkey. Central Bank Review, 20(4): 193-203.
Cai, X. J., Fang, Z., Chang, Y., Tian, S., & Hamori, S. (2020). Co-movements in commodity markets and implications in diversification benefits. Empirical Economics, 58(2): 393-425.
Elyasi, Y., & Rahimi, M. (2012). The causality between government revenue and government expenditure in Iran. International Journal of Economic Sciences and Applied Research, 5(1): 129-145.
Esener, C., Granville, B., & Matousek, R. (2022). Choosing the Optimal Tool for Fiscal Adjustment or Living under Fiscal Constraints: Panel Evidence from Selected OECD Countries. Economic Research Guardian, 12(1): 2-29.
Friedman, M. (1978). The limitations of tax limitation. Quadrant, 22(8): 22-24.
García-Albán, F., González-Astudillo, M., & Vera-Avellán, C. (2021). Good policy or good luck? Analyzing the effects of fiscal policy and oil revenue shocks in Ecuador. Energy Economics, 100, 105321.
Gençay, R., Selçuk, F., & Whitcher, B. (2003). Systematic risk and timescales. QUANTITATIVE FINANCE, 3: 108-116.
Ghysels, E., & Perron, P. (1993). The effect of seasonal adjustment filters on tests for a unit root. Journal of Econometrics, 55(1-2): 57-98.
Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society, 424-438.
Grinsted, A., Moore, J. C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear processes in geophysics, 11(5/6): 561-566.
Gurdal, T., Aydin, M., & Inal, V. (2021). The relationship between tax revenue, government expenditure, and economic growth in G7 countries: new evidence from time and frequency domain approaches. Economic Change and Restructuring, 54(2): 305-337.
Halkos, G. E., & Paizanos, E. A. (2016). Fiscal policy and economic performance: a review. Journal of Reviews on Global Economics, 5: 1-15.
Hathroubi, S., & Aloui, C. (2020). Oil price dynamics and fiscal policy cyclicality in Saudi Arabia: New evidence from partial and multiple wavelet coherences. The Quarterly Review of Economics and Finance.
Hayat, M. A., Ghulam, H., Batool, M., Naeem, M. Z., Ejaz, A., Spulbar, C., & Birau, R. (2021). Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach. Journal of Risk and Financial Management, 14(6): 1-22.
Huang, Y., Wu, H., & Zhu, H. (2021). Time-frequency relationship between R&D intensity, globalization, and carbon emissions in G7 countries: evidence from wavelet coherence analysis. Environmental Science and Pollution Research, 1-20.
Hylleberg, S., Engle, R. F., Granger, C. W., & Yoo, B. S. (1990). Seasonal integration and cointegration. Journal of econometrics, 44(1-2), 215-238.
Iiyambo, H., & Kaulihowa, T. (2020). An assessment of the relationship between public debt, government expenditure and revenue in Namibia. Public sector economics, 44(3): 331-353.
Irandoust, M. (2018). Government spending and revenues in Sweden 1722–2011: evidence from hidden cointegration. Empirica, 45(3): 543-557.
Jaén-García, M. (2020). Tax-spend, spend-tax, or fiscal synchronization. A wavelet analysis. Applied Economics, 52(28): 3023-3034.
Karlsson, H. K. (2020). Investigation of the time-dependent dynamics between government revenue and expenditure in China: a wavelet approach. Journal of the Asia Pacific Economy, 25(2): 250-269.
Kassouri, Y., Bilgili, F., & Kuşkaya, S. (2022). A wavelet-based model of world oil shocks interaction with CO2 emissions in the US. Environmental Science & Policy, 127: 280-292.
Kondoz, M., Kirikkaleli, D., & Athari, S. A. (2021). Time-frequency dependencies of financial and economic risks in South American countries. The Quarterly Review of Economics and Finance, 79: 170-181.
Linhares, F., Nojosa, G., & Bezerra, R. (2021). Changes in the revenue–expenditure nexus: confronting evidence with fiscal policy in Brazil. Applied Economics, 53(44): 5051-5067.
Loh, L. (2013). Co-movement of Asia-Pacific with European and US stock market returns: A cross-time-frequency analysis. Research in International Business and Finance, 29: 1-13.
Magazzino, C., Forte, F., & Giolli, L. (2022). On the Italian public accounts' sustainability: A wavelet approach. International Journal of Finance & Economics, 27(1): 943-952.
Managi, S., Yousfi, M., Zaied, Y. B., Mabrouk, N. B., & Lahouel, B. B. (2022). Oil price, US stock market and the US business conditions in the era of COVID-19 pandemic outbreak. Economic Analysis and Policy, 73: 129-139.
MARIMUTHU, M., KHAN, H., & BANGASH, R. (2021). Fiscal Causal Hypotheses and Panel Cointegration Analysis for Sustainable Economic Growth in ASEAN. The Journal of Asian Finance, Economics, and Business, 8(2): 99-109.
Meher, S. (2020). Dynamic Causal Relationship between Government Expenditure and Revenue in Odisha: A Trivariate Analysis, Working Paper No.78.
Mele, M., Quarto, A., & Abbafati, C. (2020). On the Fiscal Policy in Malaysia: An Econometrical Analysis Between the Revenue–and Expenditure. Res. World Econ., 11.
Meltzer, A. H., & Richard, S. F. (1981). A rational theory of the size of government. Journal of political Economy, 89(5): 914-927.
Menegaki, A. (2020). A Guide to Econometric Methods for the Energy-Growth Nexus. Academic Press.
Musgrave, R. (1966). Principles of budget determination. Public finance: Selected readings: 15-27.
Mutascu, M. (2017). The tax–spending nexus: evidence from Romania using wavelet analysis. Post-Communist Economies, 29(3): 431-447.
Obeng, S. K. (2015). A Causality Test of the Revenue-Expenditure Nexus in Ghana. ADRRI Journal of Arts and Social Sciences, 11(1): 1-19.
Payne, J. E. (1998). The tax-spend debate: Time series evidence from state budgets. Public Choice, 95(3): 307-320.
Peacock, A. T., & Wiseman, J. (1979). Approaches to the analysis of government expenditure growth. Public Finance Quarterly, 7(1): 3-23.
Polikar, R. (1999). The story of wavelets. Physics and modern topics in mechanical and electrical engineering, 192-197.
QUINTIERI, B., & Belle, M. (1997). Causality between public expenditure and taxation, evidence from the Italian case. Budgetary Policy, Modelling Public Expenditures: 214-234.
Rahaman, A., & Leon-Gonzalez, R. (2021). The effects of fiscal policy shocks in Bangladesh: An agnostic identification procedure. Economic Analysis and Policy, 71: 626-644.
Raza, S. A., Shahbaz, M., Amir-ud-Din, R., Sbia, R., & Shah, N. (2018). Testing for wavelet-based time-frequency relationship between oil prices and US economic activity. Energy, 154: 571-580.
Rösch, A., and Schmidbauer, H. (2018) WaveletComp 1.1: a guided tour through the R package. Available at: https://cran.r-project.org/web/packages/WaveletComp
Rua, A., & Nunes, L. C. (2009). International comovement of stock market returns: A wavelet analysis. Journal of Empirical Finance, 16(4): 632-639.
Sadeghi, A. (2017). Oil Price Shocks and Economic Growth in Oil-Exporting Countries: Does the Size of Government Matter. International Monetary Fund.
Sweidan, O. D. (2021). The geopolitical risk effect on the US renewable energy deployment. Journal of Cleaner Production, 293, 126189.
Tenaw, D. (2021). Getting into the details: structural effects of economic growth on environmental pollution in Ethiopia. Heliyon, 7(7), e07688.
Tiwari, A. K., Khalfaoui, R., Saidi, S., & Shahbaz, M. (2020). Transportation and environmental degradation interplays in US: new insights based on wavelet analysis. Environmental and Sustainability Indicators, 7, 100051.
Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of econometrics, 66(1-2): 225-250.
Torrence, C., & Webster, P. J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of climate, 12(8): 2679-2690.
Wildavsky, A. (1988). The new politics of the budgetary process. Glenview, IL: Scott.
Wu, T. P., & Wu, H. C. (2021). Global economic policy uncertainty and tourism of fragile five countries: Evidence from time and frequency approaches. Journal of Travel Research, 60(5): 1061-1073.
Yang, L., Tian, S., Yang, W., Xu, M., & Hamori, S. (2018). Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach. The North American Journal of Economics and Finance, 45: 116-137.