Temporal Disaggregation of the Quarterly Real GDP Series: Case of Egypt

Transcription

1 ISSN EWP /7 Euroindicators working papers Teporal Disaggregation of the Quarterly Real GDP Series: Case of Egypt Mariana Rizk

2 This paper was presented at the 6th Eurostat Collouiu on Modern Tools for Business Cycle Analysis: the lessons fro global econoic crisis, held in Luxebourg, 6th - 9th Septeber. Click here for accessing the collection of the 6th Eurostat Collouiu papers Click here for accessing the full collection of Euroindicators working papers Europe Direct is a service to help you find answers to your uestions about the European Union Freephone nuber (*): (*) Certain obile telephone operators do not allow access to 8 nubers or these calls ay be billed. More inforation on the European Union is available on the Internet ( Luxebourg: Publications Office of the European Union, ISSN EWP /7 Doi:.9/ Thee: General and regional statistics European Union, Reproduction is authorised provided the source is acknowledged. The views expressed in this publication are those of the authors, and do not necessarily reflect the official position of Eurostat.

3 Teporal Disaggregation of the Quarterly Real GDP Series: Case of Egypt Mariana Rizk * August 3, Abstract This paper ais to construct a onthly real GDP series for Egypt fro the official statistics of uarterly GDP and a set of onthly indicators, using the Chow-Lin (97) ethodology for teporal disaggregation. The best two specifications in ters of out-of-saple perforance include the consuption of oil & natural gas or the consuption of electricity as related series. Both are easured initially in real ters to avoid interediate estiation errors fro deflating noinal indicators. The predictive power of the seasonally adjusted indicators surpass that of the seasonally unadjusted, basically due to the idiosyncratic seasonal patterns of the related indicators that do not necessarily atch with that of the aggregate econoic activity. JEL Classification: C, C8, E, E3, E37 Keywords: Monthly real GDP series; teporal disaggregation; Chow-Lin procedure; forecast perforance; Egypt *Econoic analyst at the research departent of the Central Bank of Egypt, 54 Elgohoreya Street 5, Cairo, Egypt. Eail: rizkariana@hotail.co. The views contained here are of the author and do not reflect those of the Central Bank of Egypt.

4 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk Introduction Egypt s econoic growth has experienced a recovery over the period fro FY5/6 to FY7/8 with the facilitation of institutional refors and an attractive investent cliate. The real GDP growth increased fro an average of 4% over the period FY/3-FY4/5 to an average of 7% over the period FY5/6-FY7/8. The boost in growth was driven by the doestic econoy including the anufacturing, construction, trade, counications and transportation sectors; as well as the external econoy including the Suez Canal and touris sectors. In FY8/9 and the first half of FY9/, as a repercussion of the financial crisis, the growth plunged to 4.7% due to a relative slowdown in the doestic econoy - ainly anufacturing and construction - and a pronounced drop in the external sectors. The national accounts of Egypt are copiled in annual and uarterly freuencies which is the case in ost countries. The official statistics of annual GDP data are available since the 98 s, while the uarterly GDP data is published only since FY /. Meanwhile, there is a need for a higher-freuency easure of real econoic activity that helps policyakers onitor econoic developents; and allows aple observations for econoic research. A coon resort for national statistical agencies is to use a atheatical or statistical procedure to transfor the low-freuency series into higher freuency observations. This procedure is known as teporal disaggregation for flow and index variables or interpolation for stock variables. The purpose of this paper is to construct a onthly easure of real econoic activity in Egypt by disaggregating the uarterly real GDP series. The paper proceeds as follows: the first section displays a brief review of the literature. The second section introduces the ethodology used in the paper. The third section presents the results of soe data inspection. The fourth section presents the findings of teporal disaggregation and out-of-saple perforance. The final section concludes.. Literature Review The theoretical literature has outlined two alternative approaches to the teporal disaggregation of a single tie series. The first one is the purely atheatical or tie series odel such as the soothing techniue of Boot, Feibes and Lisan (967) and the ARIMA odel of Wei and Stra (99). The second approach includes ethods that ake use of related indicators observed at the desired high freuency, such as the static regression-based ethod of Chow and Lin (97) and its variants by Fernández (98) and Litteran (983). Recent developents in the literature extend the regression ethods to include a dynaic coponent such as Salazar et al. (997), Santos Silva and Cardoso (), Di Fonzo (3) and Proietti (6). Epirically, any national statistical institutes have introduced the Chow-Lin techniue in its estiation of uarterly national accounts due to its flexibility with ultiple related series, its international acceptance and the reliability of its results (Di Fonzo, 3). Moreover, any epirical applications adopted the Chow-Lin procedure or one of its variants, due to its dependence on a relatively siple regression techniue and a single autoregressive paraeter (Hall and McDerott, 7).

5 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk Quillis (5), Chen (7) and Hall and McDerott (7) estiated the uarterly GDP series by disaggregating the annual data of Spain, the Unites States and New Zealand respectively. Abeysinghe and Rajaguru (4) did the sae for China and the ASEAN4 countries (Indonesia, Malaysia, Philippines and Thailand) using the Chow-Lin ethodology or one of its variants. These studies used the relatively recently published uarterly series as a benchark to judge the uality of their estiates. Bruno et al. (5) estiated the onthly GDP series for the United States, Japan, Gerany, France, United Kingdo, Italy, Canada and the Euro area, by disaggregating the uarterly GDP. The authors eployed an out-of-saple forecasting procedure to judge the reliability of their onthly estiates, by leaving out a subsaple of the available uarterly observations and evaluating a forecast coparison criterion. For Egypt, Isail et al. (6) disaggregated the annual noinal GDP and the annual GDP deflator using different disaggregation techniues over the period The set of uarterly indicators for the noinal GDP included the Suez Canal receipts, Brent petroleu price, noinal exports and iports, M stock, noinal exchange rate, discount interest rate, and a trend variable. The results show that the Chow-Lin estiates are superior to those of Fernandez and Litteran based on the criteria of root ean suared errors and ean absolute deviations. Moursi et al. (6) estiated a onthly real GDP series for Egypt fro annual GDP data over the period 98-5 using the Litteran (983) ethodology. The set of onthly related series include Brent petroleu price, real exports and iports, real Suez Canal receipts, real M stock, real uasi-oney and the real exchange rate (with respect to the US CPI). The authors deflated the noinal indicators using the wholesale price index (WPI). Against this background, this paper adopts the Chow-Lin (97) ethodology to estiate the onthly real GDP series fro uarterly GDP data over the period :Q3-:Q. The set of related series is chosen with soe considerations. First, the set includes onthly indicators that are copiled initially in real ters. This is to avoid any interediate estiation errors in deflating the indicators especially that the WPI series is not published since 7 and the CPI series suffers fro several coputational breaks. Second, the set of indicators is chosen so as to represent the econoic activity in the ost dynaic sectors of the econoy, such as industry, ining, touris, Suez Canal, transportation and financial services. Third, the saple being inclusive of the recent global crisis period, the indicators of the highly vulnerable sectors exhibited severe breaks that led ultiately to their exclusion fro the analysis.. Chow-Lin Methodology Chow and Lin (97) introduced their regression-based techniue initially to transfor a uarterly tie series into onthly freuency. They based their techniue on a hypothetical relationship between the unobserved target onthly series y and one or ore observed onthly indicators represented as follows: y X u

6 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk where y is an (n ) vector of unobservable onthly GDP, of K onthly indicators, is a (K ) vector of unknown coefficients and X is an (n K) atrix u is an (n ) vector of stochastic errors with conditional ean zero and conditional variancecovariance atrix V. If there are T uarterly observations of GDP, then the nuber of onthly observations n is either eual to 3T or ore than 3T in case of extrapolation (forecasting an unobserved uarterly GDP figure using observations of onthly indicators). If C is a (T n) aggregation atrix then ultiplying C by any onthly atrix (n ) will yield a uarterly atrix (T ). C Then the Chow-Lin onthly relationship can be represented in the uarterly freuency as follows: y X u where y Cy, X CX and u Cu. Chow and Lin adopted a certain structure for the variance-covariance atrix V to ipleent two steps: () obtain a BLUE solution for the coefficient vector by applying the GLS estiation ethod to the uarterly regression and, () obtain the onthly residuals by disaggregating the uarterly residuals u. where CV C V. ˆ X( CV C) X( CV C) () GLS () u V C( CV C) u V C( CV C) ( y X ˆ ) Given () and (), the BLUE solution for onthly GDP by Chow and Lin (97) is: ˆ yˆ X V C( CV C) ( y X ˆ ) GLS The key assuption behind the variance-covariance atrix of Chow and Lin is that the u follows a stationary AR() process without drift: u X t u t where t is a white noise process; E( t ) = and E( t t ) =. Accordingly, the variance-covariance atrix V takes the for: GLS y GLS

7 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk V n n n3 If the autoregressive paraeter is eual to zero, then the V atrix collapses to I and the BLUE solution of the coefficient vector can be obtained by OLS. n Therefore, the Chow-Lin estiates of the high-freuency series are reliable only if the error process u is stationary or, euivalently with integrated processes, if the GDP and the related indicators are cointegrated. If this is not the case, then the GDP and related series should be differenced before teporal disaggregation as in Fernandez (98) and Litteran (983). Epirically, ost econoic tie series are integrated processes. Therefore, two approaches are used in the literature to test the necessary condition of Chow and Lin. The first is by testing for integration and cointegration for the low-freuency variables as in Abeysinghe and Rajaguru (4) and Bruno et al (5). The second approach tests for the stationarity of the high freuency residuals using Engel-Granger procedure as in Hall and McDerott (7). The underlying notion is that integration and cointegration are unchanged by teporal disaggregation (Marcellino, 999). 3. Data Inspection This section ais to identify the features of the individual tie series through graphical investigation and testing for unit roots. The data saple used coprises a set of onthly indicators and the official uarterly real GDP series. The GDP series is obtained fro the national accounts statistics published by the Ministry of Econoic Developent and is consolidated to have a new base year at FY /. The set of onthly indicators include 6 variables that easure econoic activity in several econoic sectors. The set is ainly restricted, except for soe financial indicators, to variables that are collected in real ters. The onthly indicators are obtained fro the Central Bank of Egypt and the Inforation and Decision Support Center (IDSC). By studying the graphical pattern of the related indicators (see chart A in the appendix) soe observations are worth to ention. () The oil extractions, oil products, and natural gas extractions witnessed a jup by the end of year 5 with the launch of two export projects for liuefied natural gas (LNG). () The variables regarding railway cargo and passengers show a downward trend during the study period possibly due to the network s liited coverage of the expanding industrial, coercial and entertainent areas. (3) All Suez Canal variables (oil, non-oil and total cargo) exhibited a severe drop in the afterath of the recent global crisis with the retreat in international trade and econoic activity. (4) The value of essages executed via the Local SWIFT service juped in 9 with the inclusion of corridor transactions and deposits for onetary policy purposes into the variable. Moreover, the value of autoated clearing house cheues exhibits a structural break due to the introduction of an electronic clearing syste in January 6. To conclude, being a developing country, Egypt is subject to freuent structural changes and developents n n n3

8 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk that reflect on the tie series features of its well-tracked indicators. The availability of short saples of data exaggerates these effects. The paper uses the Augented-Dickey-Fuller (ADF) and the Dickey-Fuller- Generalized-Least-Suares (DF-GLS) tests to identify the order of integration for the uarterly indicators and real GDP. The optial lag is selected according to Akaike Inforation Criterion (AIC) and the Modified Akaike Inforation Criterion (MAIC) respectively. * The tests results are not clear cut whether the order of integration is one or higher for ost of the exained variables (see table A in Appendix). It is ost likely that the low power of unit root tests and the sall nuber of observations are the causes behind such indefinite results. Based on the graphical investigation, the results of unit root tests and the findings of preliinary disaggregation attepts, the indicator list is reduced to the energy variables: oil and natural gas consuption (tons), electric energy production (kilowatt/hour), electric energy consuption (kilowatt/hour) and electric energy consuption of the industrial sector (kilowatt/hour); and tourist nights. 4. Teporal Disaggregation Results The results are assessed in two stages; first, running the estiation for the period :Q3-7:Q4 and evaluating the siple statistics of the low-freuency GLS regression, such as the t-statistics and the R suared. In the second stage, the out-of-saple forecasting procedure is used to judge the predictive power of the indicator choices (Bruno et al, 5). The uality of the forecast will be assessed in two ways. In one procedure, the estiated disaggregation is used to extrapolate the whole forecast period without changing the low-freuency estiation period. In another procedure, the estiated disaggregation is used to extrapolate three onths ahead (one-uarter forecast) of GDP, rolling through the period 8:M-:M3. The latter rolling procedure is repeated each tie after adding a uarterly observation to the low-freuency estiation period. The extrapolated values of onthly GDP are aggregated and copared to the observed value of real GDP using the root ean suared errors (RMSE) as an evaluation criterion. The indicator choice with the iniu RMSE is supposed to estiate the onthly real GDP with the highest accuracy. a. Chow-Lin Regression Results Several specifications are attepted; first by including only one related series and then cobining two related series. For each attept, the regression is run for the seasonal series and the seasonally adjusted series. The ultiplicative x- procedure is used for seasonal adjustent. With one related series (see tables and ), the coefficients of all indicators are individually significant at 5% level of significance. The seasonal regression in table show that the R-suared is the highest for the electric consuption and electric production, followed by oil and natural gas consuption; and electric consuption of * The ADF test is coonly used in the literature with the AIC and SC as criteria for lag selection. The preference of the AIC, however, is due to its ore conservative nature. The DF-GLS test has higher power especially with the use of MAIC for lag selection (Elliott et al., 996 and Ng Perron, ).

9 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk industry. However, the regression results for the seasonally adjusted series in table show that the highest R-suared is for the oil and natural gas consuption, followed by electric production, electric consuption of industry and electric consuption respectively. It is obvious that the seasonal adjustent iproves the R-suared for the energy variables, while worsens it for the tourist nights. The Engel-Granger test for cointegration shows that each related series is cointegrated with the real GDP except for the seasonally adjusted tourist nights. The estiate of the first-order autocorrelation coefficient (rho-hat) lies in the range of.3-.8 for the seasonal regressions, and for the seasonally adjusted regressions. The highest rho-hat belongs to the seasonally adjusted tourist nights. Chow-Lin Regression Results with One Related Series, Saple period: :Q3-7:Q4 t-statistics Table : Real GDP and related series are seasonal of industry production Oil & NG Tourist nights Constant (β ) Slope (β ) ˆˆ Adj. R ADF stat** Table : Real GDP and related series are seasonally adjusted using ultiplicative x- procedure t-statistics of industry production Oil & NG Tourist nights Constant (β ) Slope (β ) ˆ Adj. R ADF stat** Results are produced using the ECOTRIM software v.. of Eurostat. **ADF statistic for the uarterly residuals with lag in the first differences, no constant or trend. Critical value of MacKinnon () for 6 observations, two integrated variables, a constant in the cointegrating euation, at 5% level of significance, is In the second stage, one of the energy variables is augented with tourist nights. Note that 55% of the doestic consuption of natural gas in Egypt is used in generating electricity (IDSC database). This iplies double counting or correlation between oil and natural gas consuption on one hand and electric production or consuption on the other hand. The results in table 3 show that the coefficients of the energy variable and tourist nights are both significant in all seasonal regressions. The electric production euation has the highest adjusted R-suared, followed by electric consuption and oil and natural gas consuption. The Engel-Granger test for all seasonal regressions shows that the related series and real GDP are cointegrated. It is clear, however, that the addition of the tourist nights does not iprove the adjusted R-suared of the onerelated euation. For the seasonally adjusted regressions (see table 4), the R-suared is the highest for the seasonally adjusted oil and natural gas consuption euation. The Engel-Granger test fails to reject no cointegration for electric consuption and

10 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk electric production; while rejects it for electric consuption of industry and oil and natural gas consuption. Chow-Lin Regression Results with Multiple Related Series, Saple period: :Q3-7:Q4 t-statistics Table 3: Real GDP and related series are seasonal of industry production Oil & NG Constant (β ) Energy variable (β ) Tourist Nights (β ) ˆˆ Adj. R ADF stat** Table 4: Real GDP and related series are seasonally adjusted using ultiplicative x- procedure t-statistics of industry production Oil & NG Constant (β ) Energy variable (β ) Tourist Nights (β ) ˆˆ Adj. R ADF stat** **Critical value of MacKinnon () for 6 observations, three integrated variables, a constant in the cointegrating euation, at 5% level of significance, is b. Forecast Perforance This section exaines the predictive power of the relationships with single and ultiple related series, in both the seasonal and seasonally adjusted fors. In the first forecasting procedure the estiation period is unchanged and is used to estiate the onthly real GDP for the whole forecast period 8:M- :M3. The root ean suared errors between the aggregated onthly estiates and the observed real GDP figures show that the odels that include the consuption of oil and natural gas (with and without tourist nights) produce the best forecasts (see table 5). The seasonally adjusted estiates are superior to the seasonally unadjusted estiates. Moreover, the odels with the single related series produce ore accurate estiates of real GDP than those with ultiple related series, except for the seasonal oil and natural gas consuption. These results are consistent with the lower R- suared of the ultiple related series regressions and the poor evidence of cointegration for the ultiple regressions of electric consuption and electric production (in their seasonally adjusted fors).

11 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk Table 5: Forecast evaluation using a fixed estiation period :Q3-7:Q4 Root ean suared errors in Level ( ) Oil and NG prod. Oil and NG & Tourist Nights & Tourist Nights prod. & Tourist Nights Seasonal 3,994,35 4,3,86 5,494,6 3,68,69 5,6, 6,3,9 Multi. x-,338,84,98,7,335,384,695,855 4,,8 3,463,94 In the second forecasting procedure, the base estiation period is augented with an actual uarterly observation and used to forecast the onthly real GDP for three onths ahead (one aggregated uarter). This latter procedure is expected to better eet the needs of the policyaker and ake use of the ost recent developents in the econoy. The root ean suared errors in table 6 show that the odels that include the seasonally adjusted electric consuption as related series are superior in forecast accuracy to the odels that include the seasonally adjusted oil and natural gas consuption. Moreover, the deviations fro the actual GDP figures are lower using the rolling procedure, except for the seasonally adjusted oil and natural gas consuption. Table 6: Forecast evaluation using a rolling procedure Root ean suared errors in Level ( ) Oil and NG prod. Oil and NG & Tourist Nights & Tourist Nights prod. & Tourist Nights Seasonal 3,853,83 3,88,387 4,973,653,935,47 3,97,896 4,384,9 Multi. x-,485,35,39,48,67,86,558,9,379,37,63,66 In chart, the aggregated onthly estiate of real GDP using seasonally adjusted consuption of oil and natural gas as related series concurs with the actual figures during the period 8:Q to 9:Q3. However, in 9:Q4, it overestiates the year-over-year growth rate at 7% while it actually did not exceed 5%. Since the forecast period is basically coposed of the downturn resulting fro the recent financial crisis; and the following recovery period the odel has been able to predict the turning point in 8:Q but was delayed by one uarter in predicting the recovery in 8:Q4. For electric consuption in chart, despite that the deviations are saller for the rolling procedure, the disaggregation using the fixed estiation period was able to better predict the pattern of developent in econoic activity during the forecast period.

12 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk Quarterly y-o-y growth rates of real GDP and aggregated estiates (Seasonally adjusted by ultiplicative x-) Chart : Out-of-saple forecast using oil and natural gas consuption as related series OIL_NG_CONS_FIXED OIL_NG_CONS_ROLLING ACTUAL_GROWTH Chart : Out-of-saple forecast using electric consuption as related series ELEC_CONS_FIXED ELEC_CONS_ROLLING ACTUAL_GROWTH 5. Conclusions and Future Research The teporal disaggregation of the uarterly real GDP using the Chow-Lin ethodology yields favorable results when oil and natural gas consuption or electric consuption is used as related series. The oil and natural gas consuption variable includes the industrial, coercial and household uses. In this sense, it accounts for the developents of econoic activity fro the deand side. On the other hand, it can account for anufacturing activity and electric energy production fro the supply side (energy being a cost of production). Siilarly, the electric consuption variable includes all uses of electricity by the industrial, household and coercial sectors.

13 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk The strength of the disaggregation odel lies in its ability to predict the tiing of the recession and recovery during the past two years. However, the indefinite results of the unit root tests suggest the application of Fernandez and Litteran ethodologies in future research. References Abeysinghe, T. and Lee, C. (998), Best Linear Unbiased Disaggregation of Annual GDP to Quarterly Figures: The Case of Malaysia, Journal of Forecasting, 7, Abeysinghe, T. and Rajaguru, G. (4), Quarterly Real GDP Estiates for China and ASEAN4 with a Forecast Evaluation, Journal of Forecasting, 3, Boot J., Feibes, W. and Lisan, J. (967), Further ethods of derivation of uarterly figures fro annual data, Cahiers Econoiues de Bruxelles, 36, Bruno, G., Di Fonzo,T., Golielli, R. and Parigi, G.(5), Short-run GDP forecasting in G7 countries: teporal disaggregation techniues and bridge odels, Workshop on frontiers in bencharking techniues and their application to official statistics, Luxebourg. Chen, B. (7), An Epirical Coparison of Methods for Teporal Distribution and Interpolation at the National Accounts, Bureau of Econoic Analysis Chow, G. and Lin, A. (97), Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Tie Series by Related Series, The Review of Econoics and Statistics, 53, 4, Di Fonzo, T. (3), Teporal disaggregation of econoic tie series: towards a dynaic extension, Working papers and studies 3 edition, Office for Official Publications of the European Counities, Luxebourg. ECOTRIM software, Available online at Fernández R. (98), A ethodological note on the estiation of tie series, The Review of Econoics and Statistics, 63, Hall, V. and McDerott, J. (7), A Quarterly Post-World War II Real GDP Series for New Zealand Motu Econoic and Public Policy Research, Working Paper 7-3. Inforation & Decision Support Center (IDSC) database. Isail, M., Abdelegeed, S. and Youssef, N. (6), Teporal Disaggregation of Soe Egyptian Tie Series, Inforation & Decision Support Center (IDSC), Litteran R. (983), A rando walk, Markov odel for the distribution of tie series, Journal of Business and Econoic Statistics,, MacKinnon, J. (), Critical Values for Cointegration Tests, Queen s Econoics Departent, Working Paper No. 7. Marcellino M. (999), Soe Conseuences of Teporal Aggregation in Epirical Analysis, Journal of Business and Econoic Statistics, 7, 9 36.

14 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk Mazzi, G. L., Moauro, F. and Savio, G. (5), Theory and applications of univariate and ultivariate odels for teporal disaggregation, Working papers and studies 5 edition, Office for Official Publications of the European Counities, Luxebourg. Moursi, T. A., El Mossallay, M., and Zakareya E. (6), A Review of Conteporary Monetary Policy in Egypt, The Egyptian Cabinet -Inforation & Decision Support Center (IDSC). Proietti, T. (6), Teporal disaggregation by state space ethods: Dynaic regression ethods revisited, Econoetrics Journal, Royal Econoic Society, 9(3), Salazar, E., Sith, R. and Weale, M. (997), Interpolation using a Dynaic Regression Model: Specification and Monte Carlo Properties, NIESR Discussion Paper No, 6. Santos Silva, J. and Cardoso, F. (), The Chow-Lin ethod using dynaic odels, Econoic Modelling, 8, Wei, W. and Stra, D. (99), Disaggregation of Tie Series Models, Journal of the Royal Statistical Society. Series B (Methodological), 5, 3,

15 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk Appendix Chart A: Monthly indicators in uarterly freuency Oil and natural gas consuption Oil extractions, petroleu products and natural gas production energy production 7 4.E E+7 3.E E E+7.E E energy consuption consuption of the industrial sector consuption for household and coercial uses 3.E+7.4E+7.3E+7.8E+7 9.E+7 8.E+7.4E+7.E E+6.E E+6 7.E+6.6E E No. of railway passengers Railway passengers ties distance travelled Railway cargo 3.6E E+7 3.E E E E Railway cargo ties distance travelled Total net cargo of Suez Canal Net oil cargo of Suez Canal Net non-oil cargo of Suez Canal Tourist nights Value of essages executed via SWIFT in doestic transfers 4 4.E E E E E E+8 Value of Autoated Clearing House Cheues.4E+8.E+8.E+8 8.E+7 6.E+7 4.E

16 Teporal Disaggregation of the Quarterly Real GDP Series Mariana Rizk Table A: Unit Root Tests for uarterly GDP and uarterly indicators over period :Q3-:Q ADF t-stat (AIC) DF-GLS test statistic (MAIC) Null Hypothesis: Energy (Production & Consuption) Detrended series has a unit root First difference has a unit root GLS detrended series has a unit root First difference has a unit root Oil and natural gas consuption *** Oil extractions, petroleu products and NG production *** *** energy production * energy consuption ** consuption of the industrial sector -3.49* -3.63*** consuption for household and coercial uses Transportation/Internal Trade No. of railway passengers *** Railway passengers ties distance travelled *** Railway cargo *** *** Railway cargo ties distance travelled *** *** Suez Canal Total net cargo of Suez Canal * Net cargo of Oil ships *** Net cargo of Non-oil ships -4.43*** -3.83*** Touris Tourist nights *** Financial Transactions Value of essages executed via SWIFT in doestic transfers * Value of Autoated Clearing House cheues *** Real GDP ***indicates the rejection of the null hypothesis at % level of significance, ** 5% level of significance and * % level of significance.