Constructing Krinsky and Robb Confidence Interval for Mean and Median WTP Using Stata

The ultimate goal of most non-market valuation studies is to obtain welfare measures i.e. mean and/or median willingness to pay (WTP) and confidence intervals. While the delta (nlcom) and bootstrap (bs) methods can be used for constructing such confidence intervals in Stata, they are not recommended because WTP measures are non-linear functions of random parameters (Creel and Loomis, 1991). The best and widely used approach, which is not available in Stata, consists in simulating the confidence intervals using the Krinsky and Robb procedure (Haab and McConnell, 2002). Hole (2007) has recently introduced a useful command, wtp, which implements the Krinsky and Robb procedure in Stata, but does not feature mean and median WTP estimates and their confidence intervals. I present a Stata command, wtpcikr, which computes mean and median WTP, confidence intervals using the Krinsky and Robb procedure, achieved significance level (ASL) for testing the null hypothesis that WTP equals zero, and a relative efficiency measure (Loomis and Ekstrand, 1998). The command supports both linear and exponential contingent valuation models estimated with or without covariates using the Stata commands probit, logit, biprobit, and xtprobit. I will illustrate the use of wtpcikr by replicating empirical results in Haab and McConnell (2002).

Poverty rate and government income transfers: A spatial simultaneous equations approach

The poverty rate and income transfer are clearly correlated. However, not much research has attempted to determine the causal linkage between the two. Previous research has primarily focused on the poverty-reducing impact of income transfer. In this paper, we apply a simultaneous equation system of spatial regressions to uncover the spatial pattern of the relationship between the poverty rate and income transfer, using a sample of 3,001 U.S. counties. The results are in line with theoretical expectations; they provide evidence of a significant simultaneity effect between the poverty rate and income transfer. Our findings also confirm the presence of significant spatial autocorrelation. Contrary to previous studies, we find that more generous counties tend to do a better job of reducing poverty and that counties with more poor tend to be less generous, creating incentive for the poor to participate in the labor force. Furthermore, counties located in devolution states perform better in both poverty reduction and income transfer. These findings are missing from extant literature that focuses only on the poverty-reducing impact of welfare payments.endogeneity, income transfer, Poverty, SHAC, spatial econometrics,

Assessing Ohio's Biomass Resources for Energy Potential Using GIS

This recently completed AEDE study funded by Ohio DOD involves a geo-referenced inventory by county of Ohio biomass resources for energy. Categories include forest and crop residues, livestock manure, municipal solid waste and food processing waste. This is an update and expansion of an earlier (1982) inventory of biomass by Hitzhusen et al. It also disaggregates and expands a study by Walsh et al. in 2000 which ranked Ohio 11th among the 50 states in total biomass availability. By estimating and geo-referencing the sustainable quantities of various categories of biomass for energy by county, it is possible to identify the spatial concentrations of various biomass renewable energy feedstocks that may be economically viable for various processes for conversion. These conversion processes in turn have implications for environmental improvement and reduced dependence on foreign oil imports. A better understanding of the technical and economic pros and cons of the most promising conversion processes will be required along with further data collection and refinements of this inventory (particularly the food processing waste subset) before detailed policy recommendations can be made. However, this study is hopefully a good start toward that goal and should provide direction and focus for future analysis and recommendations for a more renewable and sustainable energy and environmental future for Ohio.Availability, Biomass energy, Crop residues, Livestock manure, Wood wastes, Municipal solid wastes.

Dealing with Internal Inconsistency in Double-Bounded Dichotomous Choice: An Application to Community-Based Health Insurance

Contingent valuation method is commonly used in the field of health economics in an attempt to help policy maker in taking decisions. The use of the double-bounded dichotomous choice format results in a substantial gain in statistical efficiency over the single bounded dichotomous choice format. Yet, this efficiency gain comes at the cost of biasness known as internal inconsistency. This paper aims at reducing this internal inconsistency in double-bounded dichotomous choice by using the certainty calibration technique in a community-based health insurance study. Findings confirm the internal inconsistency between the initial and the follow-up responses and the statistical efficiency gains of the double-bounded dichotomous choice over the single-bounded dichotomous choice. Furthermore, the use of certainty calibration reduces this internal inconsistent pattern in responses and still maintains efficiency gain. We further discuss the policy implications.Contingent valuation; internal inconsistency; certainty calibration; community-based health insurance

Assessing Ohio's Biomass Resources for Energy Potential Using GIS

This recently completed AEDE study funded by Ohio DOD involves a geo-referenced inventory by county of Ohio biomass resources for energy. Categories include forest and crop residues, livestock manure, municipal solid waste and food processing waste. This is an update and expansion of an earlier (1982) inventory of biomass by Hitzhusen et al. It also disaggregates and expands a study by Walsh et al. in 2000 which ranked Ohio 11th among the 50 states in total biomass availability. By estimating and geo-referencing the sustainable quantities of various categories of biomass for energy by county, it is possible to identify the spatial concentrations of various biomass renewable energy feedstocks that may be economically viable for various processes for conversion. These conversion processes in turn have implications for environmental improvement and reduced dependence on foreign oil imports. A better understanding of the technical and economic pros and cons of the most promising conversion processes will be required along with further data collection and refinements of this inventory (particularly the food processing waste subset) before detailed policy recommendations can be made. However, this study is hopefully a good start toward that goal and should provide direction and focus for future analysis and recommendations for a more renewable and sustainable energy and environmental future for Ohio

Assessing Ohio's Biomass Resources for Energy Potential Using GIS

This recently completed AEDE study funded by Ohio DOD involves a geo-referenced inventory by county of Ohio biomass resources for energy. Categories include forest and crop residues, livestock manure, municipal solid waste and food processing waste. This is an update and expansion of an earlier (1982) inventory of biomass by Hitzhusen et al. It also disaggregates and expands a study by Walsh et al. in 2000 which ranked Ohio 11th among the 50 states in total biomass availability. By estimating and geo-referencing the sustainable quantities of various categories of biomass for energy by county, it is possible to identify the spatial concentrations of various biomass renewable energy feedstocks that may be economically viable for various processes for conversion. These conversion processes in turn have implications for environmental improvement and reduced dependence on foreign oil imports. A better understanding of the technical and economic pros and cons of the most promising conversion processes will be required along with further data collection and refinements of this inventory (particularly the food processing waste subset) before detailed policy recommendations can be made. However, this study is hopefully a good start toward that goal and should provide direction and focus for future analysis and recommendations for a more renewable and sustainable energy and environmental future for Ohio

Ultrasound investigation of the fetal cerebral ventricles

Peer Reviewe

Solar energy research and development program on the exploitation of the solar resource on the Reunion Island and its integration into an electrical power grid

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.Reunion Island stands out by its specific energy context due to its growing population and a strong economic development. The main objective of this French region is to ensure that its exceptional potential for renewable power generation could meet an increasing energy demand. Regarding the energy development, the Regional strategy is to reach the energy independence by 2030 (SPL “Energies Réunion”) without using fossil fuels. In this context, the LE2P is leading a solar resource research programme with the aim to use solar resource as a stable source of energy and ensure its management in a reliable and efficient way for its integration into an electrical power grid. This paper aims to describe the methodology used for the development of this ambitious and challenging R&D program, projects articulation within the LE2P roadmap’s and the collaborations and partnerships initiated in UE and OI zone, permitting Eco city development especially in the IO area.cf201