Using the Aggregate Demand and Supply  Model to Identify Structural Shocks:  Results Using a Bivariate VAR

Hemmati, Abdolnaser; Mobasherpoor, Ali Reza

Using the Aggregate Demand and Supply Model to Identify Structural Shocks: Results Using a Bivariate VAR

Document Type : Original Article

Authors

Abdolnaser Hemmati ¹

Ali Reza Mobasherpoor ²

¹ Assistant Professor, Faculty of Economics, University of Tehran

² Master of Economics, University of Tehran

Abstract

This paper studied the short-run restrictions by a simple aggregate demand–aggregate supply model to identify structural shocks. Combined with the Blanchard-Quah restriction, it allowed estimation of the slope of the aggregate supply curve, the variances of structural demand and supply shocks and the extent to which structural demand and supply shocks are correlated, are estimated. Quarterly data for the period 1368:1-1385:3 were utilized in this study. This paper found that the demand and supply shocks were weakly correlated. On the other hand, the point estimate of the output-inflation tradeoff parameter, which is the slope of the short-run aggregate supply curve in the model, implies that the immediate effect on output of a structural supply shock is larger than that of an equal-sized structural demand shock. The variance decompositions also indicated that with causality from demand to supply, 25% of the short-run variation in output and nearly 9% of the long-run variation in output was the result of the structural supply shock.

Keywords

Structural VAR

Supply and Demand Shocks

Blanchard-Quah Decomposition

منابع

بانک مرکزی جمهوری اسلامی‌، حساب‌های ملی فصلی‌، سال‌های مختلف. (www.cbi.ir (
1. Enders, W., Applied Econometric Time Series. John Wiley & Sons, Inc, 1995.
2. Cover, James Peery, Walter Enders, and C. James Hueng. Forthcoming. Using the Aggregate, 2004.
3. Demand-Aggregate Supply Model to Identify Demand-Side and Supply-Side Shocks: Results from a Bivariate VAR. Journal of Money, Credit and Banking.
4. Cover, James P. and C. James Hueng. The Correlation Between Shocks to Output and the Price Level. Southern Economic Journal: 70, 2003 No. 1, July: 75-92.
5. Blanchard, Olivier Jean and Danny Quah. The Dynamic Effects of Aggregate Demand and Supply Disturbances American Economic Review 79, September 1989, 655-73.
6. Giannini, C., Topics in Structural VAR Econometrics, Berlin, Springer-Verlag, 1992.

ارقام: میلیارد ریال (قبل از تعدیل فصلی)

سال	فصل	تولید ناخالص داخلی به قیمت ثابت (1376)	تولید ناخالص داخلی به قیمت جاری	شاخص ضمنی تولید ناخالص داخلی
1367	1	42997	4447	10.34
	2	52627	6472	12.30
	3	48471	5312	10.96
	4	41194	4468	10.85
1368	1	44001	5378	12.22
	2	57809	7975	13.80
	3	50036	6624	13.24
	4	44890	5788	12.89
1369	1	50780	7301	14.38
	2	65064	10428	16.03
	3	56939	9191	16.14
	4	50881	8394	16.50
1370	1	54237	10297	18.99
	2	72955	14986	20.54
	3	67380	13223	19.62
	4	57262	11265	19.67
1371	1	66558	14000	21.03
	2	78602	19968	25.40
	3	65025	17162	26.39
	4	52355	15325	29.27
1372	1	63202	22533	35.65
	2	78737	29987	38.09
	3	64608	25114	38.87
	4	51854	22414	43.23
1373	1	56823	27036	47.58
	2	79634	39284	49.33
	3	65672	33657	51.25
	4	55368	30588	55.24

سال	فصل	تولید ناخالص داخلی به قیمت ثابت (1376)	تولید ناخالص داخلی به قیمت جاری	شاخص ضمنی تولید ناخالص داخلی
1374	1	55495	36493	65.76
	2	78442	55958	71.34
	3	69044	48629	70.43
	4	61346	44848	73.11
1375	1	61983	50564	81.58
	2	83836	73202	87.32
	3	72075	64716	89.79
	4	65202	59866	91.82
1376	1	63930	63186	98.84
	2	85340	85719	100.44
	3	75510	75541	100.04
	4	67897	68232	100.49
1377	1	65954	68840	104.38
	2	89034	97090	109.05
	3	77138	84883	110.04
	4	68574	78322	114.22
1378	1	70518	89494	126.91
	2	87313	124575	142.68
	3	80115	116666	145.62
	4	68569	105890	154.43
1379	1	71619	123232	172.07
	2	93421	167350	179.14
	3	83385	151083	181.19
	4	73854	138808	187.95
1380	1	72937	146367	200.68
	2	97450	194211	199.29
	3	86698	173457	200.07
	4	77020	157701	204.75

سال	فصل	تولید ناخالص داخلی به قیمت ثابت (1376)	تولید ناخالص داخلی به قیمت جاری	شاخص ضمنی تولید ناخالص داخلی
1381	1	81938	198045	241.70
	2	105551	258751	245.14
	3	88701	230101	259.41
	4	83025	239579	288.56
1382	1	88893	249220	280.36
	2	110182	313030	284.10
	3	96656	278051	287.67
	4	89041	269233	302.37
1383	1	93459	311492	333.29
	2	116302	390774	336.00
	3	103024	359604	349.05
	4	91550	344161	375.93
1384	1	98285	391656	398.49
	2	122113	478480	391.83
	3	106603	428013	401.50
	4	94979	403066	424.37
1385	1	104217	469997	450.98
	2	125709	545873	434.24
	3	111869	489787	437.82

Using the Aggregate Demand-Aggregate Supply Model to Identify Structural Demand-Side and Supply-Side Shocks: Results Using a Bivariate VAR

تخمین مدل VAR دو متغیره با وقفه بهینه سه Vector Autoregression Estimates Sample: 1370Q1 1385Q3 Included observations: 63 Standard errors in ( ) & t-statistics in [ ]
	DLY	DLP
DLY(-1)	-0.42512	-0.171841
	-0.115	-0.1288
	[-3.69664]	[-1.33415]
DLY(-2)	-0.45891	-0.205698
	-0.12056	-0.13503
	[-3.80642]	[-1.52336]
DLY(-3)	-0.60938	0.126242
	-0.11921	-0.13352
	[-5.11176]	[ 0.94551]
DLP(-1)	-0.04302	0.177415
	-0.12289	-0.13764
	[-0.35010]	[ 1.28897]
DLP(-2)	-0.34174	-0.071759
	-0.12303	-0.1378
	[-2.77756]	[-0.52075]
DLP(-3)	0.020608	0.190774
	-0.12031	-0.13475
	[ 0.17130]	[ 1.41581]
C	-0.02458	0.05853
	-0.03619	-0.04053
	[-0.67913]	[ 1.44405]
S1	0.124326	-0.065171
	-0.04672	-0.05233
	[ 2.66101]	[-1.24543]
S2	0.181246	-0.030671
	-0.05526	-0.06189
	[ 3.28011]	[-0.49559]
S3	-0.02539	0.018017
	-0.04808	-0.05385
	[-0.52803]	[ 0.33457]
R-squared	0.956231	0.425689
Adj. R-squared	0.948799	0.328165
Sum sq. resids	0.078998	0.099095
S.E. equation	0.038607	0.04324
F-statistic	128.6571	4.364952
Log likelihood	121.073	113.9335
Akaike AIC	-3.52613	-3.299475
SchwarzSC	-3.18595	-2.96E+00
Mean dependent	0.012505	5.20E-02
S.D. dependent	0.170621	0.052754
Determinant resid covariance (dof adj.)		2.65E-06
Determinant resid covariance		1.87E-06
Log likelihood		236.6052
Akaike information criterion		-6.876354
Schwarz criterion		-6.195994