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Licensed Unlicensed Requires Authentication Published by De Gruyter September 22, 2017

Iran’s Inflationary Experience: Demand Pressures, External Shocks, and Supply Constraints

  • Magda Kandil EMAIL logo and Ida A. Mirzaie

Abstract

This paper studies determinants of inflation in Iran. The buildup of international reserves has accelerated during the episode of higher oil price. The associated increase in government spending has limited contribution to capacity building and pronounced inflationary pressures, which accelerated at the beginning of the Iran-Iraq war in 1980, and eased at the end of the war in 1988. Accommodating monetary stance has proven to be an important determinant of inflation, both in the long and in the short-runs. In the long-run, depreciation of the rial increases the cost of intermediate goods, increasing inflationary pressures with limited significant effect on output. In contrast, depreciation could boost competitiveness of non-energy exports, in support of higher demand and output growth in the short-run. For policy implications, priorities going forward should be in place to direct both public and private resources toward relaxing binding capacity constraints, capitalizing on oil resources in Iran and the prospects of the positive implications of lifting sanctions in the context of the recent nuclear agreement between Iran and the G5+1 countries.

JEL Classification: E61; E62; E63; E32; E21

Data Appendix

Sources:

International Financial Statistics:

Real and Effective Exchange Rate of Rial

Energy Information Administration of Iran:

Iranian Light, US Dollars per Barrel

Central Bank of Iran:

Historical values of all other variables are from Iran’s Central Bank’s Economic Time Series Database. For the most recent numbers, different issues of Economic Trends and Annual Review published by Iran’s Central Bank are used.

Statistical Center of Iran:

Unemployment and Inflation Rate

Table 7:

The KPSS Statistics for Null of Level Stationary. (The 5 % critical value is 0.463)

LM Statistic (Bandwidth) +
Consumer price index0.60*(5)
Real GDP0.62* (5)
Real government spending0.21 (4)
Money supply0.53* (5)
Import price0.67* (4)
Nominal effective exchange rate0.59* (4)
  1. Test description:

  2. The KPSS (Kwiatowski, Phillips, Schmidt, and Shin) stationarity test procedure examines the null hypothesis of stationarity of a univariate time series. The KPSS test assumes that a time series variable Xt could be decomposed into the sum of a deterministic trend, a random walk, and a stationary error. Then the random walk term is assumed to have two components: an anticipated component and an error term. The stationarity of the error term is established by testing if the variance of the error is zero.

  3. If the calculated lag truncation variable is greater than 0.463, we reject the null hypothesis of stationarity.

  4. + Bandwidth is specified using Newey-West using Bartlett Kernel. For detail see Newey-West (1994).

  5. * The variable has a unit root.

Table 8:

Wald test.

VEC Lag Exclusion Wald Tests
Chi-squared test statistics for lag exclusion:
Numbers in [ ] are p-values
D(P)D(M)D(G)D(REEX)Joint
DLag 12.76653731.826991.8570921.614354172.9202
[ 0.597623][ 2.08e-06][ 0.762022][ 0.806210][ 0.000000]
DLag 231.819961.0339250.4076847.601267170.8796
[ 2.08e-06][ 0.904609][ 0.981843][ 0.107326][ 0.000000]
df444416
D(P)D(M)D(G)D(NEER)Joint
DLag 120.7902744.926106.0572122.470290379.1830
[ 0.000348][ 4.12e-09][ 0.194916][ 0.649964][ 0.000000]
DLag 223.895980.8179121.8970153.069130168.6181
[ 8.38e-05][ 0.936031][ 0.754693][ 0.546324][ 0.000000]
df444416
D(Y)D(M)D(G)D(REEX)Joint
DLag 118.1129344.665577.0138258.38194080.15134
[ 0.001173][ 4.67e-09][ 0.135159][ 0.078548][ 1.56e-10]
DLag 27.4629550.8886916.96324515.1745731.96893
[ 0.113354][ 0.926178][ 0.137843][ 0.004353][ 0.010093]
df444416
D(Y)D(M)D(G)D(NEER)Joint
DLag 112.1003348.162077.5894674.81306399.54681
[ 0.016621][ 8.73e-10][ 0.107828][ 0.307022][ 4.21e-14]
DLag 214.678210.1987114.3590045.67208554.05594
[ 0.005417][ 0.995379][ 0.359595][ 0.225012][ 5.08e-06]
df444416
Table 9:

Descriptive statistics and simple correlation across variables.

D(P)D(Y)D(M)D(G)D(REEX)D(NEER)D(Z)D(import price)
Mean4.27806.83.45E+13‒1.49E+110.02‒18.21.98.1
Std. Dev.4.916,489.65.88E+133.05E+1278.81100.46.39.6
D(P)D(Y)D(M)D(G)D(REER)D(NEER)D(Oil price)D(IMPPRICE)
D(P)10.584790.919240.2437480.00757‒0.01530.40.79407
D(Y)0.610.5291374.67E-01‒0.3218‒0.182990.20.41759
D(M)0.90.5291410.2131510.01909‒0.002980.40.62267
D(G)0.20.467380.2131511‒0.2686‒0.139180.20.16213
D(REER)0‒0.32180.019089‒0.268610.532010.1‒0.0468
D(NEER)‒0‒0.183‒0.00298‒0.139180.5320110.5‒0.0362
D(Oil Price)0.40.213710.4411710.2332550.11650.5281110.38454
D(IMPPRICE)0.80.417590.6226720.162127‒0.0468‒0.036190.41

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Published Online: 2017-9-22

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