Modeling Total Factor Productivity: the Case of Egypt

Modeling Total Factor Productivity in Developing Countries: The Case of Egypt

Ahmed Kamaly* The American University in Cairo

* Contact address: Ahmed Kamaly, The American University in Cairo, Department of Economics, P.O. Box 74, 11835 New Cairo, Egypt. Tel. +(202) 2615-4822 Fax: +(202) 2795-7565. Email: [email protected] I. Introduction and Motivation Recently, there has been a growing interest in total factor productivity (TFP) after a number of studies which have documented the importance in TFP in explaining the difference in economic growth between countries (Examples of these papers include King and Levine (1994), Prescott (1998), Hall and Jones (1999), Easterly and Levine (2001) and Islam (2003)). But when a recommendation related to TFP comes from the father of modern neoclassical growth theory definitely economists as well as policymakers interested in growth should pay utmost attention to such recommendation. In his inspirational piece Robert Solow (2001) has stressed the importance of analyzing and understanding TFP. More precisely, Solow (2001) has explicitly advocated modeling TFP through considering TFP as a left-side variable where “both technological and nontechnological” are allowed to affect TFP.

Solow (2001) was also critical of the modern growth empirics. There has been an abuse of the Solow’s growth model since the model was intended “to explain the evolution of one economy over time” with “..no explicit cross-section implications” Solow (2001, p.283). What most of the modern growth empirics did was assuming that all countries have the same level of efficiency when it comes to the allocation of inputs which is differently an unrealistic assumption. In addition, they throw a bunch of variables into the regressions “in search for empirical correlations with no analytical implications” Solow (2001, p.284).

It is worthy of noting that given the importance of TFP in shaping countries growth experiences, modeling TFP and finding the factors that affect its trend has very significant policy implications. These policy implications could be adopted by policymakers to direct TFP trend to be a substantial engine of growth especially in developing economies which are badly in need for continuously boosting their growth to ascend the development ladder.

Islam (2008) made a very good use of the first advice of Solow regarding focusing of TFP. In his study Islam (2008) has developed a well-structured and well-thought first look at TFP and its technological and nontechnological determinants. After classifying the determinants into four categories: economic, institutional, social, and physical, Islam (2008) estimated an empirical productivity model by applying it on a sample of 96 countries over the period 1960-1985.

Islam (2008) is an excellent attempt in this fundamental quest of modeling TFP and understanding its behavior. Nevertheless, Islam (2008) could not resist the temptation of cross-country analysis that runs against Solow’s second advice of focusing on one economy or a group of similar economy and study their time series trend as well as assuming that all countries are the same in terms of allocative efficiency. This paper is an attempt to follow rather stringently Solow’s advices and making use of Islam’s theoretical foundations of TFP.

2 Put it more explicitly, this study attempts to develop a simple theoretical model for TFP in a typical developing country with testable hypotheses and then make use of an actual estimation of a production function for Egypt to obtain TFP series; finally uses this series to estimate this theoretical model and examine its testable hypotheses.

This study is divided as follows. Section two gives a brief overview of the stance of the Egyptian macroeconomy with an emphasis on the trend of TFP and its contribution to economic growth. Section three develops a simple theoretical model of TFP and explores its testable hypotheses. Section four estimates this theoretical model and its testable hypotheses. Finally, section five concludes and provides a number of important policy implications.

II. Egyptian TFP and the Macroeconomy In his first conclusion, Solow (2001) stated “It may be necessary to think about genuine estimation of the underlying production function” Solow (2001, p.287). Using a consistent estimate of capital stock, Kamaly (2007) has explicitly estimated a skill- augmented production function. An important byproduct of this exercise is a coherent series of TFP in Egypt. Using this series, this section gives a brief overview of the growth experience with an emphasis on the trend of TFP and its contribution to economic growth in Egypt.

Economic growth has been quite sporadic over the past three decades in Egypt. One can divide the post war period (after the 1973 war) into three sub-periods: the Open door era, the Infitah, from 1973 until 1980; the period of imbalances and incomplete reform from 1981 until 1990; and finally, the period of structural adjustment and reforms from 1991 until the present (or 2007 in our sample).

After the 1973 war and with the implementation of open door policy, Infitah, Egypt witnessed a surge in output growth financed by a flux of foreign currency inflows from oil revenue, tourism receipts, workers remittances and foreign aid. During this period until 1980, Egypt recorded its highest level of economic growth during the last 30 years with an impressive 13.3% average annual output growth (See Table 1). This remarkable growth experience was driven by a high level of investment which enabled the real stock of capital to grow at a striking rate of 16.5% per annum (See Table 2). Also this period witnessed a salient performance of TFP which was responsible for 17% of output growth matching the contribution of human capital (See Table 7 in Kamaly, 2007).

Delineating TFP growth is not as easy as explaining the accumulation of capital stock during the 1970s. Handoussa el al. (1986) studied productivity change in public enterprises during the Infitah and reported a similar increase in TFP. They argued that the spur in aggregate demand and relaxation of the constraints on imports led to an improvement in productivity as firms began to utilize their idle capacity which existed prior to 1973. This explanation can be extended to the whole economy given that firms

3 during this period were predominantly publicly owned. As for the few private enterprises which existed before or appeared after 1973, most of these firms benefited from the opening up of the economy as they were able to import technical and non- technical technological improvement which added positively to their productivity1.

One of the main problems of the Egyptian economy during this period was its strong dependency on external sources to finance economic growth leaving the Egyptian rentier economy (Abdel-Fadil, 1979; Beblawi 1987) quite susceptible to external shocks. This susceptibility to external shocks and capital flows swings increased the variability of investment as well as TFP which were transmitted to output (Table 3). During this period, the government together with the rest of Egyptians did not mind much this variability of income as it was accompanied by prosperity for the majority of the population. Moreover, it is evident now that the government did not take advantage of this manna to build the foundation of a more sustainable growth and to reduce the reliance on unsustainable external windfalls. Instead it continuously pushed the limit of its spending beyond its means producing a growing deficit which was financed by inflation tax and foreign borrowing.

The beginning of the 1980s brought with it draught in the springs of foreign capital mainly due to the drop in the oil prices and political instability. The government continued its extravagant expenditure path even faced with a constant drop in its revenue. Indeed, there were pressures on the regime to continue this inconsistent path. For one, and after almost a decade following the launch of the Infitah, the bulk of investment and employment opportunities were still provided by the public sector. The government could not just stop investing in its public sector enterprises or stop its guaranteed employment scheme as the private sector was not fit enough to take on the slack and assume a leading role in the economy. In addition, during the 1980s, the government invested heavily in basic infrastructure such as power, communication, roads and sewage (See Figure 1) which was on the verge of a complete break down in the beginning of the 1980s (Harik, 1996). Despite its necessity, this huge investment in infrastructure projects did not produce any immediate improvement in TFP since the effect of infrastructure projects usually comes with a significant lag. In fact, the stock of capital in Egypt has increased by 10.4% per annum whereas TFP registered approximately a 1% annual decrease over the period 1981-1990.

During the period from 1973 until the beginning of the 1980s, Egypt had enjoyed a period of high level of income growth maintained by generous external inflows masking feeble fundamentals, structural imbalances and shaky economic base which was further weakened by the aura of a classical case of the Dutch disease. Around the mid 1980s,

1 Technical technological improvement is the kind of productivity enhancement techniques embodied in the newly installed capital. Non-technical technological improvement, however, is not necessarily associated with new capital. It is the kind of productivity improvement associated with advances in institutional setup, management skills and work culture and norms whether on a micro level or on a macro level.

4 the shortage in foreign inflows exposed the major flaws in the Egyptian economy which manifested into huge government deficit, double digit inflation and mounting foreign debt. This again was quite damaging to TFP to the extent that TFP contributed negatively to growth during the second sub-period, 1981-1990 (See Table 6 in Kamaly, 2007). Hence, one can conclude that a combination of heavy infrastructure investment and ailing economy resulted into a negative productivity growth during the 1980s.

The final period of analysis, 1991-2007, started with TFP reaching an abyss in 1991. However, this specific year marked the launch of the Economic Reform and Structural Adjustment Program (ERSAP) in Egypt designed to stabilize macroeconomic imbalances, eliminate pricing distortion, and transform the economy from a centrally planned economy to a market-based open economy where the private sector assumes the leading role. The implementation of ERSAP was aided by the writing-off of 50 percent of foreign debt by the Paris club after Egypt’s assistance to the collision in the Second Gulf war.

ERSAP was quite successful in stabilizing the macroeconomy and eliminating many price distortions plaguing different sectors of the economy. As a result, the economy was revitalized and the growth in output reversed its downward trend and assumed an upward path (See Figure 2). However, as observed in most of the stabilization programs, the boom period was short-lived and it was followed by a bust around the end of the 1990s. Despite the initial revival in investment in the beginning of the period, the growth in capital stock was quite disappointing with an average of a mere 4% annually compared to 16% and 10% during the first and the second sub-periods respectively. As a result, the contribution of capital stock to output dropped to 49% down from almost 90% in the previous sub-period. However, if it were not for TFP, output growth would have been even weaker especially after 1997. TFP change has shown positive development during this last sub-period raising its contribution in output growth to almost 13%.

There are a number of possible reasons behind this positive contribution of TFP in growth. Comparing the last sub-periods with the other two previous periods, one can safely assert that economic fundamentals have improved, market distortions were minimized, the financial sector has been developed, the private sector has been revived, and the strong dependency on windfall rents has been reduced.

III. A Simple Model of TFP Despite the fact that growth theory is relatively silent when it comes to the determinants of TFP, Islam (2008) has jumpstarted this important topic by proposing that the determinants of productivity can be grouped into two broad categories:

5 economic factors and non-economic factors. The latter includes institutions, social base and physical base2. (1) Where denotes economic factors, denotes institutional variables and represents both social and physical base. Notice that the latter set of variables are time invariant since both social and physical base variables only differ from one country to another over the short to the medium run.

Islam (2008) has introduced the idea of a link from physical and human capital to productivity which he labeled as “feedback effect”. According to this effect, factors accumulation has two channels to affect growth; directly through the production function and indirectly through its effect on TFP. This “feedback effect” is in fact quite intuitive. For example, the accumulation of human capital through better education and training should have positive spillover effect on productivity aside from its direct positive effect on output as one of the factor inputs.

Focusing on developing countries or less developed countries, one can safely claim that these countries are net importers of technology. Despite its increase from 0.8 percent in 2002 to 1 percent in 2007, R&D expenditure as a ratio of GDP in developing countries is well below the same ratio for developed countries amounted to 2.2 and 2.3 percent in 2002 and 2007 respectively3 (UNESCO, 2010). In addition, in most of these countries, most of the expenditure on R&D originates from the government and is used to support inefficient administrative body that usually impedes not encourages research.

This low national expenditure on R&D coupled with the inherit inefficiency of public expenditure make the production of knowledge and technology insignificant in most of developing and in all the less developed countries. If these countries have limited capacity in improving productivity, then it must be the case that most of the improvement in productivity comes from abroad embodied in the imported capital.

The above analysis hypothesizes a direct link between imported capital (machinery, tools, etc) and TFP, where higher amount of imported capital is associated with positive change in TFP. Moreover, it is more likely that this relation between the imported capital and TFP is a lagged one. Installing new foreign technology is less likely to have a contemporaneous effect on TFP; rather it takes time to install the new imported capital, integrate it with the old capital and fully utilize its advantageous characteristics and superior productivity.

2 There is no sacred classification of the determinants of productivity; for example, Rodrik et al. (2004) classified productivity determinants into policies, institutions and geography. 3 Less developed countries spend even more dismal amount on R&D in absolute and relative terms. According to UNESCO (2010) the gross domestic expenditure on R&D as a percentage of GDP is a mere 0.2 percent.

6 One then can use the idea of “feedback effect” and the one associated with the imported capital to come out with a more specific model for productivity.

Where denote capital stock, human capital, imported capital and other economic factors respectively. Examples of include macroeconomic variables which may affect the productivity in the economy such as inflation rate, foreign direct investment (FDI), openness, etc. Notice that equation (2) specifies that most of the explanatory variables are assumed to affect productivity with a lag.

IV. Estimation Results This section takes the simple theoretical model developed in the previous section and uses time series data on Egypt to estimate an empirical version of this theoretical model.

Kamaly (2007) has produced a consistent estimate of the Egyptian capital stock and then has used this series to genuinely estimate a skill-augmented production function for Egypt. In this study, the results of this production function estimation are used to generate productivity series. This “two-stage” methodology is exactly what Solow (2001) has recommended using to produce TFP estimate4.

Table 3 depicts a number of statistical characteristics of the change in TFP series (CTFP) during the period 1976-20075. The most important results are first CTFP is stationary variable (It is an I(0) process); second, one can reject that hypothesis that CTFP is normally distributed.

Estimating (2) using a time series data for Egypt involves removing variables since they are time invariant. We use the change in real capital stock lagged and the log of literacy rate in Egypt lagged to capture the “feedback effect”. Also we use the change in the ratio of imported capital to total imports lagged to capture the suggested hypothesis of spillover effect form imported capital to productivity.

As appearing in Table 4 under the first regression results, all the above three explanatory variables are significant at least at the 5 percent level with the overall estimated regression is significant at the 1 percent level. According to the estimated coefficients, there is a “feedback effect” from human capital to productivity. This means that an improvement in human capital-proxied by literacy rate- has dual effect of

4 Islam (2008) has used this “two-stage” methodology but his productivity measures are estimates for large sample of countries which are not based on genuine estimation of an underlying production function for each country. Hence the criticisms of Solow (2001) regarding cross-section regressions still apply. 5 Since the actual implementation of the Open door policy, Infitah, was around the mid 1970s, 1976 was chosen to be the beginning of our sample. 7 growth. One through the accumulation of factor input; and the other one is indirect through its positive effect on productivity which in turns leads to more growth. This result seems to confirm the Nelson and Phelps (1966) approach which argues that human capital enhances growth via its positive effect on the ability of countries to use and benefit from technological innovations.

As for the coefficient of capital stock, surprisingly enough it has a negative sign. This means that an increase in the capital stock, i.e. more investment is associated with a decline in productivity in Egypt. Could this be the result of the massive investment in infrastructure in the 1980s which was discussed in section two of this study, or from ill- suited types of investment that are not compatible with Egypt’s comparative advantage or just a statistical anomaly especially that its statistical significance is relatively low?

The significance and the sign of the ratio of imported capital total imports attest that our proposed hypothesis is true that there exists a direct link between imported capital (machinery, tools, etc) and TFP. According to this result, imported capital has a dual effect on growth. First, it adds to the capital stock which directly increases output and second, it has a spillover effect on TFP which again adds positively to output.

Under category, a number of other economic variables including inflation, real output growth, FDI, ratio of government expenditure to GDP, and infrastructure indicators were added to the regression; however, despite picking up the right, all these variables signs were found to be totally insignificant. Regression 2 in Table 4 depicts the results of including lagged inflation rate in the regression.

Modeling how institutions can affect TFP is not an easy task in time series analysis as almost all institution variables are not available in long time series and if they do, their time series variation is minimal. To deal with this deficiency, we tried several dummies to capture the change in institutional setup in Egypt like for instance dividing the sample into two periods before 1991 and after corresponding to before adopting stabilization and reform policies and after. Most of these proxies turned out to be insignificant; however, when a dummy presenting the regime of the late president Sadat6 along with the log of oil price lagged7 were tossed into the regression, they turned to be significant as presented by regression 3 in Table 4.

According to the obtained results, first, it seems that Sadat regime had better institutions promoting productivity gain vis-à-vis Mubarak regime. Second, oil price has a negative and significant effect on productivity in Egypt. Hence, an increase in the price of oil produces a negative change in productivity similar to the one observed in developed countries as documented by Jorgenson (1988). This result could be driven by

6 This dummy takes the value of 1 during Sadat regime and zero during current president Moubarak. 7 Oil price is a very good proxy for institutional change in Egypt. The increase in the price of oil after the first oil shock has drastically changed the norms, customs and hence institutions in Egypt especially with waves of Egyptians seeking employment in the booming oil exporting countries (Amin, 2001).

8 some negative offshoots of rent-seeking activities associated with Dutch-disease common during oil booms or from contagion passed to the Egyptian economy from developed economies which usually experience a loss in productivity in times of oil price surge. This last explanation is indeed plausible given the verification of the hypothesized link between imported capital and productivity and the fact that Egypt is considered a net importer of technology from the developed world.

V. Conclusion and Policy Implications This study develops a theoretical model for productivity determinants in developing countries following the advices and recommendations of Solow (2001) and the groundbreaking work of Islam (2008) in analyzing and examining TFP. The study then uses a consistent estimate of TFP series obtained from a genuine estimation of a production function for Egypt (Kamaly 2007) to estimate this theoretical model and examine its testable hypothesis. In addition, this study looks at TFP series in the broad context of the Egyptian macroeconomy during three distinct phases starting from the 1975 until 2007. .

The behavior and the contribution of TFP in growth have found to vary from one phase to another. The launch of the open door policy, Infitah, brought with it tremendous gain in productivity which aided average growth to reach record high levels during the post-war period until 1980. This upbeat trend in TFP during this period could be possibly attributed to the increase in effective demand which led to the utilization of idle capacity existed prior to the 1973 war. Another possible reason is the opening up of the economy and the realized benefits from tapping into imported superior technology and production techniques. This euphoria in TFP came to an end during the subsequent period which witnessed a strong reversal in the positive trend of TFP leading it to contribute negatively to growth during the 1980s period until the initiation of ERSAP in 1991. Again, there are a number of possible factors that contributed to this dismal trend of TFP. Structural imbalances, feeble fundamentals, lavish price distortions and palpable dependency on external finance all have brought down TFP especially after a series of external shocks which dried up the springs of external inflows. Despite the encouraging beginnings after the launch of ERSAP in terms of output, capital accumulation and productivity, the economy reverted to its murky path. The only exception however has been the trend of TFP which has been overall positive.

Estimation results reveal the presence of a “feedback effect” from factor inputs to productivity as hypothesized by Islam (2008). Human capital proxied by literacy rate is found to have a significant positive effect on TFP. This implies that investing in human capital does not only benefit growth from the usual direct way through factor inputs channel but also from an indirect channel through its positive effect on productivity which shifts upward the production function. Strangely enough, capital stock has found to have a negative but not very significant effect on productivity. Possible reasons behind this strange finding other then a statistical anomaly are the massive investment

9 in infrastructure in the 1980s which was discussed in section two of this study, and ill- suited types of investment that have little to do with Egypt’s comparative advantage but were the outcomes of the existence of a number of price distortions throughout the analysis period.

One of the main contributions of this paper is the theoretical development and empirical verification of a channel from imported capital to productivity in developing countries. According to this channel, imported capital has a spillover positive effect on productivity since imported capital is usually bundled with superior technology which bears productivity gains. This channel appears to be very strong since developing and less-developed countries invest so little in R&D; hence most of the improvement in productivity is not generated from within the country but has foreign source.

In terms of institutional dimension, results have shown that in the case of Egypt regime change has an effect on productivity. More precisely, late president Sadat regime appears to be more conducive to productivity gains vis-à-vis present Moubarak regime. But more importantly, it was found that higher oil prices hinder productivity in Egypt similar to the pattern observed in developed countries. Could this result be driven by a simple statistical anomaly; or some negative offshoots of rent-seeking activities associated with the Dutch-disease; or simply passed to the Egyptian economy from developed economies which usually experience a loss in productivity in times of oil price surge? This last explanation resonates well with the discovered link between imported capital and productivity. Nevertheless, regardless of the explanation behind the negative association between oil prices and productivity in Egypt, one should not presume that higher oil price is a panacea. Rather, higher oil prices may depress productivity, hence crowding out, at least to some extent, the positive effect of the expected flux in capital inflow.

10 REFERENCES

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12 Table 1: Real Output Growth

PERIOD TOTAL GROWTH (%) AVERAGE GROWTH (%) 1973-1980 106 13.3 1981-1990 61.3 6.1 1991- 2007 77 4.5

Table 2: Capital Stock, Augmented Labor and TFP Growth

PERIOD CAPITAL STOCK (%) AUGMENTED LABOR TFP (%) (%)* 1973-1980 16.5 4.3 2.3 1981-1990 10.4 4.5 -0.8 1991- 2007 4.1 3.9 0.7 * For augmented labor, 1981 is included in the first period to counter affect some data anomaly in the total number of workers series (see Kamaly, 2007 for more discussion)

Table 3: Basic Statistical Characteristics of CTFP

MEAN 0. 008 Augmented DF (CTFP has a tstatis= -5.37 unit root) Probability (0.00) Standard Deviation 0. 0313 Skewness 1.244 Coefficient of Variation 3.9125 Kurtosis 4.7182 Skewness/Kutosis combined test stat 10.21 Probability (0.0061)

13 Table 4: Modeling CTFP

(1) (2)8 (3) Constant -0.3301 -0. 2109 -0. 3718 (-3.46)*** (-1.08) (-1.08) -0.0715 -0. 0591 -0. 1274 (-2.66)** (-1.78)* (-3.65)* 0.3197 0. 2503 0. 5193 (3.24)*** (1.75)* (4.37)*** 0.2884 0.2896 0. 2496 (4.76)*** (4.52)*** (4.22)*** -0.0754 (-0.78) -0..0223 (-2.73)** 0.0458 (1.67)* R-squared 0.56 0.57 0.64

Fstats 13.83** 11.1*** 14.63***

D-Wstats 2.465 2.473 2.702 Notes: t-statistics are in brackets. *** Significant at 1% level or more, ** significant at 5% level or more, * significant at the 10% level or more. N=32. Regressions’ results are reported with Newey-West (robust) standard errors.

8 Very similar results to (2) if growth in output is included instead of inflation.

14 Figure 1: Ratio Infrastructure to GDP

Figure 2: Output Growth and TFP Change