Has Algeria Suffered from the Dutch Disease? Evidence from 1960-2016 Data

Abstract

Algeria is strongly dependent on oil exports revenues to fuel its economy and following the 1986 oil counter-shock this country has experienced a persistent decline of its manufacturing sector. Although it has benefited from high oil prices over the last decades and implemented a myriad of economic reforms, Algeria has failed to develop its manufacturing sector and diversify its economy. One of the main mechanisms through which fluctuations in oil prices can constitute an impediment to the development of the manufacturing sector, and hence to long-term growth, in an economy that heavily relies on a natural resource exports is referred to in the literature as the Dutch disease. This paper aims to test whether or not Algeria's economy has suffered from the main symptoms of this syndrome by analyzing data covering more than half-a-century. More specifically, we use annual data from 1960 to 2016 and investigate two important implications of this phenomenon that occur following an oil boom, namely, the spending effect and the resource movement effect. We perform some simple tests of these signs of the Dutch disease using a set of regressions while controlling for some other factors that could have led to similar economic symptoms. The results do not allow us to unambiguously claim that the Algerian economy has suffered from the Dutch disease over the period under study.

Oil Prices and the Algerian Exchange Rate: Is there any Difference with Hidden Co-Integration?

“…Jbir and Zouari (2011) depending on quarterly data covering the period 1995Q1-2007Q3; had tried to examine the relationship between oil prices and the Algerian Dinar exchange rate under the Dutch Disease, and they found that the increase in the inflation rate due to oil price shocks is the main cause of the real exchange rates appreciation in the short term according to the oil prices shocks. This study was repeated by Gasmi and Laourari (2017) for yearly data covering the period 1960-2013 using an ARDL model to test the co-integration relationship between real oil prices and the real effective exchange rate of the Algerian Dinar, to examine a robust long-run relationship among the two variables controlled by relevant variables (productivity differential; government expenditure; net foreign assets; terms of trade; share of the manufacturing sector in GDP; inflation rate; real GDP per capita and degree of openness). The main result of the study is that there is no evidence at the 5% significance level of a co-integration relationship among the variables which led them to reject the support of the spending effect as a symptom of the Dutch disease.…”

40 Years of Dutch Disease Literature: Lessons for Developing Countries

“…Based on annual data for Algeria for 1960–2016, Gasmi and Laourari ( 2017 ) test for the presence of a cointegration relationship between the Algerian real effective exchange rate and a set of parameters that includes international oil prices. Using an ARDL Bound Approach, they reject the hypothesis of a cointegration relationship among the variables, which they interpret as evidence that no spending effect occurred in Algeria, an oil-exporting country.…”

“…Having concluded that there was an absence of an appreciation effect caused by international oil prices in Algeria, Gasmi and Laourari ( 2017 ) also test the direct impact of oil prices on manufacturing sector growth. Based on an ARDL model, they find a positive impact of the real effective exchange rate on the manufacturing sector, but a negative impact of oil price on the manufacturing sector, both in the short and in the long term.…”

Real Exchange Rate Misalignment and Economic Growth: The Case of Trinidad and Tobago

“…To estimate Equation 1, we implement the Autoregressive Distributed Lag (ARDL) approach to assessing cointegration, i.e., whether a long run relation exists amongst our variables, which was introduced by Pesaran and Smith (1995) and further developed by Pesaran et al (2001). We choose to utilize this model over other cointegration tests such as the Johansen cointegration test given the number of advantages of using the ARDL approach, which are outlined by Pesaran et al (2001), Acaravci and Ozturk (2012) and Gasmi and Laourari (2017). A major benefit to utilizing this model is that it can be applied irrespective of whether the series under investigation are stationary at I(0) or I(1) or a mixture of both.…”

“…A major benefit to utilizing this model is that it can be applied irrespective of whether the series under investigation are stationary at I(0) or I(1) or a mixture of both. In contrast to the Johansen cointegration procedure, the ARDL approach can accommodate different orders of integration of the variables and pre-testing for a unit root is only necessary to ensure there are no I(2) variables, (Salim et al 2015;Gasmi and Laourari 2017;Nguyen 2017). Another advantage of the ARDL model is the fact that it takes into account the error correction model, which enables the model to simultaneously estimate both short and long-run coefficients, (see Pesaran et al 2001;López Villavicencio and Bara 2008;Sami and Kreishan 2012).…”