of June , the National Council for .. l6 This action was also recommended in CONPES () “Plan de expansidn portuaria. surveys. From through , Colombia’s competitiveness ranking by the World Specifically, CONPES put more emphasis on the. Document CONPES of Document CONPES of De scribe any training or capacity‑building programmes for government officials.
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In addition, they use their estimates to assess the extent to which the distortions in housing prices associated with the subsidy-stratification system affect final subsidy beneficiaries. Intuitively, their exercise provides a fe of calculating how much more people pay for houses located in areas with higher subsidies for public utilities DPS.
Thus, in a sense, the estimation strategy provides the value that individuals place on higher subsidies. Clearly, from the policy point of view, it seems very important to understand the distortions associated with the cross subsidy system and the specific stratification strategy that guides subsidy assignment. From both these perspectives, this paper is an important contribution. The basic estimation strategy is to estimate a relatively standard hedonic price model in which public utility subsidies received or paid by a given dwelling have an effect on the price of the house, controlling for a conpe of observed characteristics of the house and the neighborhood.
The key issue dealt with in the paper is the endogeneity of the subsidy in such ocnpes equation.
E-GOBERMENT by william alexander rojas parra on Prezi
In other words, estimating the causal effect of DPS subsidies on housing prices is difficult because houses that receive high subsidies are located in lower socioeconomic strata that is, poorer neighborhoods conpds thus are associated with lower prices. Similarly, houses that receive low subsidies or pay contributions are located in higher socioeconomic strata that is, richer neighborhoods and thus are associated with higher prices.
Thus in the data one will observe that the higher the subsidy, the lower the price of the house.
As a result, the estimate of the effect of the subsidy on housing prices could be biased in this particular example, one would expect the estimate to be downwardly biased in a simple OLS ordinary least squares estimation that does not account for the unobserved characteristics of houses and neighborhoods that are also associated with housing prices.
The critical issue is, then, that all [End Page 87] relevant characteristics pertaining to house, neighborhood, and stratum are not observed 3229 measured. Unobserved variables, for example, would con;es the provision of public goods at the stratum level or neighborhood characteristics within and across strata.
To deal with this issue, the authors implement a type of regression discontinuity design RDD by taking advantage of the stratification system by which cknpes are assigned to one of six socioeconomic strata that are then used to target differential subsidies for public utility services. In particular, the estimation strategy consists of using strata boundary dummies to account for any unobserved characteristics shared by houses on either side of the boundary.
Clearly, for this design to conppes valid, one would require that subsidies make a discrete jump at the boundaries while neighborhoods continue to change in a smooth manner at the boundaries. Intuitively, the authors claim that while there is significant heterogeneity across strata and, as expected, homogeneity within stratum the location of the exact boundaries can be arbitrary to a great extent because a very large number of dwellings were assigned to very few groups dde in total.
Therefore, one cannot expect these boundaries to perfectly divide fundamentally different neighborhoods. Thus the authors argue that it is plausible to expect characteristics of households and neighborhoods to be quite similar at the boundaries. However, one must dd aware of the fact that the key assumption of the regression discontinuity design would be plausible in cases in which boundaries are determined according to characteristics uncorrelated with the independent variables in the hedonic price equation and, in particular, the subsidy, which is the variable of interest and the unobserved error term.
However, in this case, it is clear that considerations about socioeconomic characteristics of houses, households, and neighborhoods are crucial in determining the boundaries. The results reported in the paper indicate that, in fact, even for houses located very close to the boundary, at least 50 percent of the observed characteristics of dwellings are statistically conpew different on both sides of the boundary.
These results might suggest that the stratification If you would like to authenticate conprs a different subscribed institution that supports Shibboleth authentication or have your own login and fonpes to Project MUSE, click ‘Authenticate’.
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