An empirical analysis of energy demand in Namibia

Abstract

Using a unique database of end-user local energy data and the recently developed Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration, we estimate the long-run elasticities of the Namibian energy demand function at both aggregated level and by type of energy (electricity, petrol and diesel) for the period 1980 to 2002. Our main results show that energy consumption responds positively to changes in GDP and negatively to changes in energy price and air temperature. The differences in price elasticities across fuels uncovered by this study have significant implications for energy taxation by Namibian policy makers. We do not find any significant cross-price elasticities between different fuel types.JEL Classification: Q41; Q42; Q48.

Residential electricity demand dynamics in Turkey

“…There are also many examples of multivariate cointegration procedures of Johansen (1988), Johansen and Juselius (1990), and Johansen's (1996) full information maximum likelihood technique. De Vita et al (2006) provides an extensive survey of the econometric procedures applied in the empirical studies of energy demand. A recent single cointegration approach, known as autoregressive-distributed lag (ARDL) of Pesaran et al (2001), has become popular amongst the researchers.…”

Long-run relationship among transport demand, income, and gasoline price for the US

“…Note: * denotes statistical significance at the 1% level. 1936-20061954-3.89 LPRICE 1919-20061991-3.41 LGDP 1919-20061939-7.20* LREG 1940-20061955-4.46 LMFU 1980-20061990.63* Note: * statistical significance at the 1% level. LPRICE 1946-1977& 1978-1990-0.40 0.69 1978-1990& 1991-2006-2.40 0.024 1946-1977& 1991-2006-1.20 0.24 LVMT 1946-1977& 1978-1990 3.07 0.00 1978-1990 & 1991-2006 -1.80 0.083 1946-1977 & 1991-2006 -0 …”

“…Graham and Glaister (2002) provided an update; but of the studies they cited, only four involved cointegration, 1 and none focused on the US. Likewise, the few studies since that review that employ conintegration have focused on countries other than the US, e.g., Brazil (Alves and Bueno, 2003), Greece (Polemis, 2006), Namibia (De Vita et al, 2006), and South Africa (Akinboade et al, 2008). Furthermore, only one previous cointegration analysis estimated a genuine long-run relationship: Bentzen (1994) As noted, spatial intensity influences transport demand; however, since the area of the US has remained constant over the period studied (albeit, US territories Alaska and Hawaii became states in 1959), population density simply increases with increases in population, and thus, is not an appropriate variable for a time series study like this one.…”

Energy prices, multiple structural breaks, and efficient market hypothesis

“…The first is to accommodate structural breaks. Ever since [30] WTI and Brent Lee et al [29] 1991-2004 (Weekly data) Non-Stationarity Vita et al [53] Namibia ADF and Perron [7] 1980-2002 Non-stationarity Holtedahl and Joutz [55] World [17] test. M and Q denotes monthly and quarterly data, respectively.…”