**Table 3. Econometric Models of Infrastructure Needs**

||**Paved**<br>**Roads**|**Total**<br>**Roads**|**Rails**|**Ports**|**Telephone**<br>**mainlines**|**Mobile**<br>**lines**|**Electricity**<br>**generation**|
|---|---|---|---|---|---|---|---|
|**Method**|Probit for<br>grouped<br>data|Fixed<br>Effects|Fixed<br>Effects|Fixed<br>Effects|Logit for<br>grouped<br>data|Logit for<br>grouped<br>data|Fixed<br>Effects|
|Per capita GDP|-0.261***<br>(0.00188)|0.111*<br>(0.0575)|-0.0107<br>(0.0422)|1.124***<br>(0.164)|0.983***<br>(0.000166)|0.414***<br>(0.000175)|0.652***<br>(0.0549)|
|Share of manufactures<br>in GDP|0.131***<br>(0.00183)|0.00209<br>(0.0435)|-0.0428<br>(0.0395)|0.152<br>(0.111)|0.0686***<br>(0.000178)|-0.142***<br>(0.000197)|0.199***<br>(0.0343)|
|Share of agriculture in<br>GDP|-0.179***<br>(0.00197)|-0.0772<br>(0.0491)|0.0630<br>(0.0393)|-0.202*<br>(0.121)|0.199***<br>(0.000153)|0.184***<br>(0.000186)|0.147***<br>(0.0429)|
||-0.574***|-0.427***|-0.929***|0.409|-0.00914***|2.133***|-0.00847|
|Populationdensity|(0.00459)|(0.116)|(0.102)|(0.298)|(0.000294)|(0.000354)|(0.100)|
|Urbanization|-0.493***<br>(0.00541)|0.377***<br>(0.137)|-0.0421<br>(0.112)|0.279<br>(0.337)|3.361***<br>(0.000515)|1.259***<br>(0.000530)|0.141<br>(0.0872)|
||||||-1.645***|-0.828***||
|Populationgrowth|||||(0.00133)|(0.00157)||
|Time trend|0.0985***<br>(0.000500)|-5.684<br>(4.146)|-1.224<br>(1.304)||||0.0697***<br>(0.0126)|
|||0.00714|0.00155|||||
|Time trend squared||(0.00519)|(0.00164)|||||
|Market age||||0.102***<br>(0.0121)|0.107***<br>(1.37e-05)|0.111***<br>(1.69e-05)||
|||||-0.00117***|-0.00366***|0.00414***||
|Market age squared||||(0.000235)|(3.78e-07)|(5.67e-07)||
||-35.32***|1,128|236.2|-15.28***|-8.373***|-13.74***|-34.94***|
|Constant|(0.191)|(828.6)|(260.0)|(2.094)|(0.00281)|(0.00287)|(4.722)|
|Observations|_A_|633|551|496|_a_|_a_|1,034|
|R-squared||0.119|0.540|0.801|||0.459|
|Numberofcoefficients||172|109|102|||173|

_Notes:_ Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1. All relevant variables are in logarithms. _a_ indicates a large number of observations due to the grouped technique.

Projected levels of infrastructure stocks are valued at the unit costs used in Yepes (2008) and shown in Table 4. Time dummies and country fixed effects are used in order to proxy differences in infrastructure prices. In the case of telecommunications and ports, a market age variable accounts for the speed of technological change across countries. Lagged dependant variables are included to eliminate the structural part of interest. Analysis of spurious regressions have been made as in the literature showing that a structure of lagged variables as in Arellano and Bond estimations can eliminate all variance thus eliminating the structural part of interest (Yepes, Pierce and Foster, 2008).

The models are estimated on a worldwide dataset, although with a partial coverage of regions including MENA. The database used for these estimations is an annual panel data of infrastructure stocks, macroeconomic variables, and demographic characteristics (see for details the data annex). Data for MENA countries covers years up to 2008. The data are taken mainly from the World Bank’s World Development Indicators (WDI) complemented with material from 5