The role of money in influencing real economic activities has been a long-standing debate in macroeconomics. As per the Keynesian theory, household consumption expenditure plays a significant role in promoting economic growth. Given the rapid consumption-led growth pattern in the emerging Asia Pacific region, in this article, we attempt to assess the role of money in influencing household consumption expenditure, which propels economic growth. We employ a panel data set from 2005–2018 for 10 emerging Asian economies, covering Bangladesh, Cambodia, India, Indonesia, Malaysia, Pakistan, Philippines, Sri Lanka, Thailand and Vietnam. Given the region’s heterogeneous nature, we employ a variant of the popular St Louise equation model with autoregressive distributed lag model (ARDL) panel framework based on pooled mean group (PMG) and dynamic fixed effect (DFE) models developed by Pesaran and Shin to study the underlying relationships. Both PMG and DFE models suggest a strong positive relationship between money and household consumption expenditure both in the long run and short run. After allowing for control variables such as government final consumption expenditure and interest rate, the relationships continue to hold steady. Further, the relationship holds true across both narrow (M1) and broad money (M3) measures. The government final consumption expenditure and interest rates do not have influence on household consumption expenditure in the long run, but they have an influence in the short run.
AhmedE., & JohannesJ. M. (1984). St. Louis equation restrictions and criticisms revisited: Note [Note]. Journal of Money, Credit, and Banking, 16(4), 514–520. https://doi.org/10.2307/1992189
2.
AndersenL. C., & JordanJ. L. (1968). Monetary and fiscal actions: A test of their relative importance in economic stabilization. Federal Reserve Bank of St Louis Review, 50(11), 11–24.
3.
ArellanoM., & BoverO. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29–51. https://doi.org/10.1016/0304-4076(94)01642-D
4.
AsteriouD., PilbeamK., & PratiwiC. E. (2021). Public debt and economic growth: Panel data evidence for Asian countries. Journal of Economics and Finance, 45(2), 270–287. https://doi.org/10.1007/s12197-020-09515-7
5.
BarthJ. R., & BennettJ. T. (1974). A note on the relationship between FEBS and GNP. Economic Inquiry, 12(3), 403–405. https://doi.org/10.1111/j.1465-7295.1974.tb00408.x
6.
BattenD. S., & ThorntonD. L. (1983). Polynomial distributed lags and the estimation of the St. Louis equation. Review, 65(4), 13–25. https://doi.org/10.20955/r.65.13-25.pmo
7.
BattenD. S., & ThorntonD. L. (1986). The monetary-fiscal policy debate and the Andersen-Jordan equation. Review, 68(8), 9–17. https://doi.org/10.20955/r.68.9-17.itk
8.
BelliveauS. (2011). A St. Louis equation to in one place: Reassess the influence of macroeconomic-policy instruments [MPRA Paper no. 28839]. Retrieved July 26, 2020, from https://mpra.ub.uni-muenchen.de/28771/1/MPRA_paper_28771.pdf
9.
BiasP. V. (2014). A chronological survey of the Friedman—Meiselman/Andersen—Jordan single equation debate. Research in Business and Economics Journal, 10, 1–21.
10.
BlackburneE. F., & FrankM. W. (2007). Estimation of nonstationary heterogeneous panels. STATA Journal: Promoting Communications on Statistics and Stata, 7(2), 197–208. https://doi.org/10.1177/1536867X0700700204
11.
BlinderA. S., & SolowR. (1974). Analytical foundations of fiscal policy. In A. S. Blinder (Eds.), The economics of public finance. Brookings Institution Press.
12.
BosworthB. (2014). Interest rates and economic growth: Are they related?SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2443845
13.
BreitungJ. (2000). The local power of some unit root tests for panel data, Advances in Econometrics, Volume 15: Nonstationary panels, panel cointegration, and dynamic panels (pp. 161–178). JAY Press.
14.
ChaitipP., ChokethawornK., ChaiboonsriC., & KhounkhalaxM. (2015). Money supply influencing on economic growth-wide phenomena of AEC open region. Procedia Economics and Finance, 24, 108–115. https://doi.org/10.1016/S2212-5671(15)00626-7
15.
ChoiI. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20(2), 249–272. https://doi.org/10.1016/S0261-5606(00)00048-6
16.
CorriganG. (1970). The measurement and importance of fiscal policy changes. Federal Reserve Bank of New York Monthly Review, 52(6), 133–145.
17.
DavisR. (1969). How much does money matter? A look at some recent evidence. Federal Reserve Bank of New York Monthly Review, 51(6), 119–131.
18.
De LeeuwF., & KalchbrennerJ. (1969). Monetary and fiscal actions: A test of their relative importance in economic stabilization-comment. Federal Reserve Bank of St. Louis Monthly Review, 51(4), 6–11.
19.
FriedmanM., & MeiselmanD. (1963). The relative stability of monetary velocity and the investment multiplier in the United States, 1897–1958. In Commission on money and credit: Stabilization policies (pp. 165–268). Prentice Hall.
20.
GoldfeldS. M., BlinderA. S., KarekenJ., & PooleW. (1972). Some implications of endogenous stabilization policy. Brookings Papers on Economic Activity, 1972(3), 525–640. https://doi.org/10.2307/2534128
21.
HabibullahM. S., & EngY. (2006). Does financial development cause economic growth? A panel data dynamic analysis for the Asian developing countries. Journal of the Asia Pacific Economy, 11(4), 377–393. https://doi.org/10.1080/13547860600923585
22.
HadriK. (2000). Testing for stationarity in heterogeneous panel data. Econometrics Journal, 3(2), 148–161. https://doi.org/10.1111/1368-423X.00043
23.
HaferR. W. (1982). The role of fiscal policy in the St. Louis equation. Federal Reserve Bank of St. Louis Monthly Review, 64(1), 17–22. https://doi.org/10.20955/r.64.17-22.bvk
24.
Hamad AlgaeedA. (2016). Money supply as a conduit of the consumption in the Saudi economy: A co-integration approach. International Journal of Economics, Finance and Management Sciences, 4(5), 269–274. https://doi.org/10.11648/j.ijefm.20160405.16
25.
HarrisR. D. F., & TzavalisE. (1999). Inference for unit roots in dynamic panels where the time dimension is fixed. Journal of Econometrics, 91(2), 201–226. https://doi.org/10.1016/S0304-4076(98)00076-1
26.
ImK. S., PesaranM. H., & ShinY. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7
JordanJ. L. (1986). The Andersen-Jordan approach after nearly 20 years. Federal Reserve Bank of St. Louis Review, 68(8), 5–8. https://doi.org/10.20955/r.68.5-8.gzc
KootR. S. (1977). On the St. Louis equation and an alternative definition of the money supply. The Journal of Finance, 32(3), 917–920. https://doi.org/10.1111/j.1540-6261.1977.tb01999.x
31.
LaidlerD. (1978). Money and money income: An essay on the ‘transmission mechanism’. Journal of Monetary Economics, 4(2), 151–191. https://doi.org/10.1016/0304-3932(78)90001-6
32.
LevinA., LinC., & ChuC. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24.
33.
MarshallM., & CokeO. (2016). A sectoral analysis of e-money consumption and growth. Social and Economic Studies, 65(2/3), 69–98.
34.
ModiglianiF., & AndoA. A. (1976). Impacts of fiscal actions on aggregate income and the monetarist controversy: Theory and evidence. In J. Stein (Ed.). Proceedings of the Brown University Conference on Monetarism, Amsterdam.
35.
OnoS. (2012). Financial development and economic growth: Evidence from Russia. Europe–Asia Studies, 64(2), 247–256. https://doi.org/10.1080/09668136.2012.635484
PesaranM. H., ShinY., & SmithR. P. (1999). Pooled mean group estimation of dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621–634. https://doi.org/10.1080/01621459.1999.10474156
38.
SamargandiN., FidrmucJ., & GhoshS. (2015). Is the relationship between financial development and economic growth monotonic? Evidence from a sample of middle-income countries. World Development, 68, 66–81. https://doi.org/10.1016/j.worlddev.2014.11.010
39.
SimionescuM., BalcerzakA. P., BilanY., & KotáskováA. (2018). The impact of money on output in Czech Republic and Romania. Journal of Business Economics and Management, 19(1), 20–41. https://doi.org/10.3846/jbem.2018.1480
40.
TavlasG. S. (1981). Keynesian and monetarist theories of the monetary transmission process. Journal of Monetary Economics, 7(3), 317–337. https://doi.org/10.1016/0304-3932(81)90032-5
41.
TonbyO., WoetzelJ., ChoiW., SeongJ., & WangP. (2019). Asia’s future is now. Retrieved July 30, 2020, fromhttps://www.mckinsey.com/featured-insights/asia-pacific/asias-future-is-now
42.
TsaiS., & ChangT. (2018). The co-movement between money and economic growth in 15 Asia-Pacific countries: Wavelet Coherency analysis in time-frequency domain. Journal for Economic Forecasting, 0(2), 63–79.
43.
WangH. (2019). In 2020, Asian economies will become larger than the rest of the World combined - here’s how. Retrieved July 25, 2020 fromhttps://www.weforum.org/agenda/2019/07/the-dawn-of-the-asian-century/
