More Like this

1. Estimating the impacts of natural gas power generation growth on solar electricity development: PJM's evolving resource mix and ramping capability

   https://doi.org/10.1002/wene.454  

   Nyangon, Joseph ; Byrne, John ( July 2022 , WIREs Energy and Environment)

   Expansion of distributed solar photovoltaic (PV) and natural gas‐fired generation capacity in the United States has put a renewed spotlight on methods and tools for power system planning and grid modernization. This article investigates the impact of increasing natural gas‐fired electricity generation assets on installed distributed solar PV systems in the Pennsylvania–New Jersey–Maryland (PJM) Interconnection in the United States over the period 2008–2018. We developed an empirical dynamic panel data model using the system‐generalized method of moments (system‐GMM) estimation approach. The model accounts for the impact of past and current technical, market and policy changes over time, forecasting errors, and business cycles by controlling for PJM jurisdictions‐level effects and year fixed effects. Using an instrumental variable to control for endogeneity, we concluded that natural gas does not crowd out renewables like solar PV in the PJM capacity market; however, we also found considerable heterogeneity. Such heterogeneity was displayed in the relationship between solar PV systems and electricity prices. More interestingly, we found no evidence suggesting any relationship between distributed solar PV development and nuclear, coal, hydro, or electricity consumption. In addition, considering policy effects of state renewable portfolio standards, net energy metering, differences in the PJM market structure, and other demand and cost‐related factors proved important in assessing their impacts on solar PV generation capacity, including energy storage as a non‐wire alternative policy technique.

   This article is categorized under:

   Photovoltaics > Economics and Policy

   Fossil Fuels > Climate and Environment

   Energy Systems Economics > Economics and Policy

    

   more » « less
2. Bivariate Kernel Deconvolution with Panel Data

   https://doi.org/10.1007/s13571-020-00226-x  

   Basulto-Elias, Guillermo ; Carriquiry, Alicia L. ; De Brabanter, Kris ; Nordman, Daniel J. ( April 2020 , Sankhya B)

   We consider estimation of the density of a multivariate response, that is not observed directly but only through measurements contaminated by additive error. Our focus is on the realistic sampling case of bivariate panel data (repeated contaminated bivariate measurements on each sample unit) with an unknown error distribution. Several factors can affect the performance of kernel deconvolution density estimators, including the choice of the kernel and the estimation approach of the unknown error distribution. As the choice of the kernel function is critically important, the class of flat-top kernels can have advantages over more commonly implemented alternatives. We describe different approaches for density estimation with multivariate panel responses, and investigate their performance through simulation. We examine competing kernel functions and describe a flat-top kernel that has not been used in deconvolution problems. Moreover, we study several nonparametric options for estimating the unknown error distribution. Finally, we also provide guidelines to the numerical implementation of kernel deconvolution in higher sampling dimensions.

    

   more » « less
3. Estimating the Socioeconomic Impacts of Flooding on Regional Economies With a Computable General Equilibrium Model

   https://doi.org/10.1029/2022WR033474  

   Parent, Olivier ; Hofe, Rainer vom ; Oh, Seunghoon ; Ervin, Paul ; Khalid, Md Atikul ; Yeghiazarian, Lilit ( August 2023 , Water Resources Research)

   The growing number of flood events in urban areas is causing far‐reaching economic losses and social disruptions. To implement suitable flood risk management strategies and measures for flood prevention and mitigation, it is paramount to adequately assess economy‐wide losses associated with potential flood events. The assessment of potential flood damage in the USA relies significantly on the Federal Emergency Management Agency (FEMA) Hazus Flood Model. A primary requirement to reduce uncertainty is to empirically gather user input data. Consequently, there is a need to integrate publicly accessible business data for accurate evaluation of losses in business activities. We present a novel approach for estimating both the direct losses in business activities during a flood and the total economy‐wide impact that arise from these disruptions. First, we integrate the FEMA Hazus Flood Model with Reference Solutions business‐level data to estimate the reduction in business activities (i.e., direct losses) following a 100‐year flood event in New Hanover County, North Carolina. Second, we estimate the broader economy‐wide impact these business activity losses have on total industry output, employment, value‐added and household income using a regional computational general equilibrium model. The advantage of our approach is the easy replicability of the business loss estimation process for US cities and regions of interest, which, when used in a follow‐up economic impact study, leads to estimating the total economy‐wide losses in economic activities. Policy makers relying solely on direct physical and economic damages would, by ignoring indirect losses, underestimate the benefits of investing in flood mitigation and protection.

    

   more » « less
4. A Catch-22—the Test–Retest Method of Reliability Estimation

   https://doi.org/10.1093/jssam/smad043  

   Tufiş, Paula A. ; Alwin, Duane F. ; Ramírez, Daniel N. ( December 2023 , Journal of Survey Statistics and Methodology)

   This article addresses the problems with the traditional reinterview approach to estimating the reliability of survey measures. Using data from three reinterview (or panel) studies conducted by the General Social Survey, we investigate the differences between the two-wave correlational approach embodied by the traditional reinterview strategy, compared to estimates of reliability that take the stability of traits into account based on a three-wave model. Our results indicate that the problems identified with the two-wave correlational approach reflect a kind of “Catch-22” in the sense that the only solution to the problem is denied by the approach itself. Specifically, we show that the correctly specified two-wave model, which includes the potential for true change in the latent variable, is underidentified, and thus, unless one is willing to make some potentially risky assumptions, reliability parameters are not estimable. This article compares the two-wave correlational approach to an alternative model for estimating reliability, Heise’s estimates based on the three-wave simplex model. Using three waves of data from the GSS panels, which were separated by 2-year intervals between waves, this article examines the conditions under which the wave-1, wave-2 correlations which do not take stability into account approximate the reliability estimate obtained from three-wave simplex models that do take stability into account. The results lead to the conclusion that the differences between estimates depend on the stability and/or fixed nature of the underlying processes involved. Few if any differences are identified when traits are fixed or highly stable, but for traits involving changes in the underlying traits the differences can be quite large, and thus, we argue for the superiority of reinterview designs that involve more than 2 waves in the estimation of reliability parameters.

    

   more » « less
5. Assessing the local economic impacts of land protection

   https://doi.org/10.1111/cobi.13318  

   Sims, Katharine R. E. ; Thompson, Jonathan R. ; Meyer, Spencer R. ; Nolte, Christoph ; Plisinski, Joshua S. ( April 2019 , Conservation Biology)

   Land protection, whether public or private, is often controversial at the local level because residents worry about lost economic activity. We used panel data and a quasi‐experimental impact‐evaluation approach to determine how key economic indicators were related to the percentage of land protected. Specifically, we estimated the impacts of public and private land protection based on local area employment and housing permits data from 5 periods spanning 1990–2015 for all major towns and cities in New England. To generate rigorous impact estimates, we modeled economic outcomes as a function of the percentage of land protected in the prior period, conditional on town fixed effects, metro‐region trends, and controls for period and neighboring protection. Contrary to narratives that conservation depresses economic growth, land protection was associated with a modest increase in the number of people employed and in the labor force and did not affect new housing permits, population, or median income. Public and private protection led to different patterns of positive employment impacts at distances close to and far from cities, indicating the importance of investing in both types of land protection to increase local opportunities. The greatest magnitude of employment impacts was due to protection in more rural areas, where opportunities for both visitation and amenity‐related economic growth may be greatest. Overall, we provide novel evidence that land protection can be compatible with local economic growth and illustrate a method that can be broadly applied to assess the net economic impacts of protection.

    

   more » « less