Public Works as a safety net

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188      Public Works as a Safety Net

particularly if the information can be cross-checked and complemented by administrative records.

Measuring Aggregate Impact Measuring the aggregate impact of public works is a difficult task and is thus not typically undertaken. There are, however, a few examples of impact evaluation that show the overall positive impact of those public works programs that use a higher percentage of labor intensity than that applied to a typical infrastructure program. Ramilison and Randrianarison (2007) use a macroeconomic model to assess the comparative advantage of using high-labor intensity versus high-mechanical intensity in public works programs in Madagascar. They found that high-labor intensity programs have a much higher level of value-added consumption, household income, and job creation than high-mechanical intensity programs (table 7.5). This higher level derives largely from the indirect contribution of high-labor intensity. Alternatively, a computable general equilibrium model can be used to measure broader impacts on macroeconomic variables such as net jobs created, income redistribution, and so on. Using this approach, Narayana, Parikh, and Srinivasan (1991) found the aggregate impact of public works programs to be highly beneficial to poor households. Table 7.5  Comparative Analysis of the Investment Impact of Infrastructure Work in Madagascar Description of components considered Total value added Consumption Household income Public deficit   Public expenditure   Public revenue Import duty Tax on goods and services Income tax Balance of trade Job creation Coefficient

High-labor intensity Effect Direct Indirect Total

High-mechanical intensity Effect Direct Indirect Total

72.7 60.2 72.7 –155.3 –164.4 9.1 8.4 0.0 0.7 –91.7 54,276 —

170.9 191.0 230.7 15.6 0.0 15.6 8.9

243.7 251.2 303.5 –139.7 –164.4 24.7 17.4

35.8 29.7 35.8 –152.3 –164.4 12.1 11.8

84.2 94.1 113.6 7.7 0.0 7.7 4.4

120.1 123.8 149.5 –144.6 –164.4 19.8 16.2

4.6 2.1 –97.4 96,814 —

4.6 2.7 –189.0 151,090 1.48

0.0 0.3 –128.6 26,746 —

2.3 1.0 –48.0 47,707 —

2.3 1.3 –176.5 74,452 0.73

Source: Ramilison and Randrianarison 2007. Note: Measured in ariary billions. — = not available.


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