Are International Food Price Spikes the Source of Egypt’s High Inflation?

Abstract

This paper examines whether domestic inflation spikes in Egypt during 2001–2011 were primarily the result of external food price shocks. To estimate the pass-through of international food price inflation to domestic price inflation, two different methodologies are used: a two-step regression model estimates the pass-through in the long run, and a VAR model provides the short-run estimates. The empirical evidence confirms that pass-through is high in the short term, but not in the long run. More precisely, our results show that (1) Long-run pass-through to domestic food inflation is relatively low, lying between 13 % and 16 %, while the long-term spill-over from domestic food inflation to core inflation is moderate, lying around 60 %; (2) In the short-term, pass-through is relatively high, estimated around 29 % after 6 months and around two-thirds after a year, but the spill-over effect to core inflation is limited; (3) international food price shocks explain only a small portion of domestic inflation shocks in both the short and long terms; and (4) international price inflation has asymmetric effects on domestic prices.

Appendices

Annex 1: Data Description and Sources

• International food price indices: three indices are used from the IMF, FAO food, and FAO cereals.

• Domestic Prices: The time series of Egypt’s CPI and domestic food prices are constructed by the authors for a unified base year (1999/2000 = 100) using official data from the Central Agency for Public Mobilization and Statistics (CAPMAS) that are available for different base years.⁶ Domestic non-food prices time series are constructed by the authors by excluding the food component (the weight of which is 42.6 %) from the CPI. The index of core prices (1999/2000 = 100) is constructed by the authors from CPI data by excluding food and energy components from the CPI (the weight of which are respectively 42.6 % and 3.1 %). The Central Bank of Egypt (CBE) core inflation measure (which excludes only fruits and vegetables and regulated prices) is only available since 2005 only. Also, the non availability of this level of disaggregated price data did not allow the authors to extend the CBE core inflation time series. Non-food and core prices were measured using the following formulas:

  $non-food=\frac{{\left[ {CPI-\left( {foodCPI*{w_f}} \right)} \right]}}{{\left( {1-{w_f}} \right)}}$, where ${w_f}$ is the weight of food in the CPI basket.

  $core=\frac{{\left[ {CPI-\left( {foodCPI*{w_f}} \right)-\left( {energyCPI*{w_e}} \right)} \right]}}{{\left( {1-{w_f}-{w_e}} \right)}}$, where ${w_e}$ is the weight of energy in the CPI basket.

• Economic Activity: In the absence of monthly data on Egypt’s GDP the authors proxied output by an index constructed by the means of principal components analysis using seven seasonally adjusted real activity variables: real exports of goods, cement production, steel production, oil production, industrial consumption of electricity, Suez Canal tonnage, and the number of tourists. Variables are turned into indices. As the obtained series had in some cases negative values, a positive integer of ‘5’ was added to all the variable’s observations. The output gap (ygap) is constructed by applying the Hodrick-Prescott (HP) filter under the assumption that output fluctuates around its potential level.⁷ The HP filter decomposes output into permanent and transitory components generating a smoothed trend of output. These generated series are the estimated potential output. The ygap is calculated as the difference between actual and potential output as a percentage to potential output.

• Exchange rate and monetary policy: The nominal exchange rate (LE/US$), an important cost factor and affects prices, is obtained from the International Financial Statistics (IFS). To calculate the real exchange rate, the authors used the formula: $q={e }*(\frac{{pp{i_{us }}}}{{cp{i_{eg }}}})$, where (q) is the real exchange rate, (e) is the nominal exchange rate, ($pp{i_{us }}$) is the foreign price level, proxied by the US producer price index for all commodities, and $(cp{i_{eg }})$ is the domestic price level, proxied by the CPI in Egypt. Data on the US PPI is from the US Bureau of Labor Statistics.

  The M2 in LE millions (excluding foreign currency deposits), a measure of money to allow for the effects of monetary policy and also for the relationship between money and domestic prices, is obtained from the Central Bank of Egypt.⁸

Annex 2: Unit Root Tests

Variable	ADF statistic	Order of integration	McKinnon critical values for rejection of hypothesis of a unit root
			1 %	5 %	10 %
Annualized log differences (except for ygap)
CPI	−7.64	I(0)	−3.48	−2.88	−2.58
Food CPI	−8.09	I(0)	−3.48	−2.88	−2.58
Core	−10.9	I(0)	−3.48	−2.88	−2.58
IMF	−7.52	I(0)	−3.48	−2.88	−2.58
FAO	−5.88	I(0)	−3.48	−2.88	−2.58
FAO cereals	−5.88	I(0)	−3.48	−2.88	−2.58
M2d	−8.25	I(0)	−3.48	−2.88	−2.58
Real er	−9.31	I(0)	−3.48	−2.88	−2.58
ygap	−6.36	I(0)	−3.48	−2.88	−2.58

Table 4.1 reports the ADF unit root test results for a lag of 12 months (based on the Schwartz information criterion (SIC)). The tests included a constant. As shown in the table, all variables in the log-difference form are stationary (i.e. I(0)).

Annex 3: Lag Length

To determine the lag length, a lag order selection test was conducted. The computation of the lag order for a maximum lag of 12 months produced a discrepancy among the different criteria. Based on the on the likelihood ratio (LR) criterion, the VAR is estimated with four lags to allow for enough endogenous transmission of the shocks in the system.

VAR lag order selection criteria
Endogenous variables: FOODINFW2 YGAP CPIINF2 M2DVAR RERCHANGE
Exogenous variables: C
Date: 11/28/11 Time: 10:46
Sample: 2000 M07 2011 M07
Included observations: 120
Lag	LogL	LR	FPE	AIC	SC	HQ
0	347.82	NA	2.27e-09	−5.71	−5.60	−5.67
1	412.73	123.34	1.17e-09a	−6.38a	−5.68a	−6.10a
2	431.55	34.18	1.30e-09	−6.28	−5.00	−5.76
3	449.99	31.97	1.46e-09	−6.17	−4.30	−5.41
4	473.09	38.12*	1.52e-09	−6.13	−3.70	−5.1
5	492.60	30.56	1.69e-09	−6.04	−3.02	−4.82
6	512.98	30.23	1.87e-09	−5.97	−2.37	−4.50
7	538.79	36.13	1.91e-09	−5.98	−1.80	−4.28
8	554.68	20.92	2.34e-09	−5.83	−1.07	−3.89
9	575.36	25.50	2.68e-09	−5.76	−0.41	−3.59
10	596.50	24.31	3.10e-09	−5.69	0.23	−3.29
11	625.49	30.93	3.21e-09	−5.76	0.75	−3.12
12	646.45	20.61	3.91e-09	−5.69	1.39	−2.81

1. LR sequential modified LR test statistic (each test at 5 % level)
2. FPE final prediction error
3. AIC akaike information criterion
4. SC schwarz information criterion
5. HQ hannan-Quinn information criterion
6. ^aindicates lag order selected by the criterion

VAR lag order selection criteria
Endogenous variables: FOODINFW2 YGAP FOODINF2 COREINF M2DVAR RERCHANGE
Exogenous variables: C
Date: 11/28/11 Time: 10:57
Sample: 2000 M07 2011 M07
Included observations: 120
Lag	LogL	LR	FPE	AIC	SC	HQ
0	356.44	NA	1.17e-10	−5.84	−5.70a	−5.78
1	435.15	148.24	5.75e-11a	−6.55a	−5.58	−6.15a
2	468.15	58.86	6.07e-11	−6.50	−4.69	−5.77
3	491.06	38.55	7.64e-11	−6.28	−3.64	−5.21
4	529.89	61.49	7.44e-11	−6.33	−2.85	−4.92
5	554.95	37.17	9.24e-11	−6.15	−1.83	−4.39
6	589.80	48.21	9.93e-11	−6.13	−0.97	−4.04
7	647.37	73.88a	7.47e-11	−6.49	−0.50	−4.06
8	677.52	35.68	9.14e-11	−6.39	0.44	−3.62
9	702.43	26.98	1.26e-10	−6.21	1.46	−3.09
10	740.30	37.24	1.47e-10	−6.24	2.26	−2.79
11	791.01	44.80	1.46e-10	−6.48	2.85	−2.69
12	830.89	31.24	1.87e-10	−6.55	3.63	−2.42

1. LR sequential modified LR test statistic (each test at 5 % level)
2. FPE final prediction error
3. AIC akaike information criterion
4. SC schwarz information criterion
5. HQ hannan-quinn information criterion
6. ^aindicates lag order selected by the criterion