Published Papers

  • Avelino, A. (2017). Disaggregating Input-Output Tables in Time: the Temporal Input-Output Framework, Economic Systems Research, 29(3), 313-344. pdf-icon-32x32    <codes & datasets>
  • Carrascal, A., Avelino, A., and Franco, A. (2017). Gray water and environmental externalities: International patterns of water pollution through a structural decomposition analysis, Journal of Cleaner Production,  165, 1174-1187. pdf-icon-32x32      <codes & datasets>
  • Avelino, A., Baylis, K., and Honey-Rosés, J. (2016). Goldilocks and the Raster Grid: Selecting Scale when Evaluating Conservation Programs, PLOS ONE, 11(12).  pdf-icon-32x32


Working Papers

  • 1. The Challenge of Estimating the Impact of Disasters: many approaches, many limitations and a compromise 

(submitted as a chapter for the second edition of the book Modeling Spatial and Economic Impacts of Disasters)

Andre F. T. Avelino and Geoffrey J. D. Hewings

Abstract: The recent upward trend in the direct costs of natural disasters is a reflection of both an increase in asset densities and the concentration of economic activities in hazard-prone areas. Although losses in physical infrastructure and lifelines are usually spatially concentrated in a few areas, their effects tend to spread geographically and temporally due to production chains and the timing and length of disruptions. Since the 1980’s, several techniques have been proposed to model higher-order economic impacts of disruptive events, most of which are based on the input-output framework. However, there is still no consensus for a preferred model to adopt. Available models tend to focus on just one side of the market or have theoretical flaws when incorporating both sides. In this paper, the Generalized Dynamic Input-Output framework (GDIO) is presented and its theoretical basis derived. It encompasses the virtues of intertemporal dynamic models with the explicit intratemporal modeling of production and market clearing, thus allowing supply and demand constraints to be simultaneously analyzed. Final demand is endogenized via a demo-economic extension to study the impact of displacement and unemployment post-disaster. The key roles of inventories, expectation’s adjustment, primary inputs, labor force and physical assets in disaster assessment are explored and previous limitations in the literature are addressed. It will be shown that the dynamic Leontief model, the sequential interindustry model and the traditional input-output model are all special cases of the GDIO framework.

Tags: Natural disasters, Production chain disruptions, Input-output, Higher-order effects

  • 2. Comparing the economic impact of natural disasters generated by different input-output models. An application to the 2007 Chehalis River Flood (WA)

         (revise and resubmit to Risk Analysis)

Andre F. T. Avelino and Sandy Dall’erba

Abstract: Due to the concentration of assets in disaster-prone zones, changes in risk landscape and in the intensity of natural events, property losses have increased considerably in recent decades. While measuring these stock damages is common practice in the literature, the assessment of the economic ripple effects due to business interruption is still limited and available estimates tend to vary significantly across models. Given the myriad of proposed input-output models in the disaster literature, this paper reviews the most used methodologies (the traditional Leontief model, Cochrane’s rebalancing algorithm, the sequential interindustry model, the dynamic inoperability input-output model and its inventory counterpart) and compares the total losses they generate. We also highlight the nuances of the input-output framework that have been overlooked by applied researchers. As a common benchmark, we analyze the first and higher-order flow effects of the Chehalis river flood that took place in Washington State in 2007. In order to quantify the direct damages, we rely on fine-scale water depth-grids from the U.S. Army Corps of Engineers and the widely used HAZUS software. The results indicate a difference of 69% to 115% in the estimation of total losses across models, hence a careful model selection based on the characteristics of the disaster, of the affected region(s) and on the knowledge of the inoperability and intersectoral interdependency is needed. Such efforts will help us understand the level of vulnerability of our economic systems and be better prepared for future events.

Tags: Flood, Economic Impact, Input-Output

  • 3. Revisiting the Temporal Leontief Inverse: new insights on regional structural change

(revise and resubmit to Economic Systems Research)

Andre F. T. AvelinoAndre Carrascal Incera and Alberto Franco Solís

Abstract: The current availability of longer series of national/regional input-output tables, as well as the release of global input-output databases, has led to a growing body of the literature analyzing changes in the economic structure and their drivers. The most common technique applied is the structural decomposition analysis (SDA), a comparative statics exercise between two periods. Given SDA’ static nature, however, we cannot extract the evolution of industrial linkages from a time-series of annual input-output tables to understand the source of these changes. In response to such limitations, Sonis and Hewings (1998) proposed an alternative methodology denoted the Temporal Leontief Inverse (TLI). In contrast to a traditional SDA, the TLI focuses on industrial linkages only, but offers a dynamic framework to analyze their change. The evolutionary path of an industry’s multiplier and the contribution of the rest of the economy to it can be traced through the temporal changes in the fields of influence. However, Sonis and Hewings’ formulation only accounted for the simultaneous change in the whole economy from period to period. Hence, one could not isolate the contribution of a particular sector (or set thereof) to this evolutionary path to more precisely understand the underlying sources of its variation. In this paper, we modify the original formulation and devise a linear decomposition of the annual change to address the latter concerns. In a single region setting, we can isolate the contribution of structural changes in direct input requirements by sectors or group of sectors. In a multiregional setting, we can study the contribution of trade, foreign countries and technology to a particular industry. The methodology is illustrated by uncovering some hidden effects not captured in the application of the original TLI to Chicago by Okuyama et al. (2006). Finally, we combine the SDA with the extended TLI to introduce dynamics in the decomposition of technical changes.

Tags: Temporal Inverse, Structural Decomposition Analysis, Input-Output, Time Series

  • 4. A Social-Environmental Regional Sequential Interindustry Economic Model for Energy Planning: Evaluating the Impacts of New Power Plants in Brazil 

Andre F. T. Avelino, Geoffrey J. D. Hewings and Joaquim J. M. Guilhoto

Abstract: Energy planning is a multidimensional problem as it affects the economy, environment and local population in a spatially heterogeneous fashion. In this paper, we propose an integrated social-environmental economic model for energy planning analysis that estimates economic, emissions and public health impacts at different regional levels. By combining the traditional I-O framework with electrical and dispersion models, dose-response functions and GIS data, our model aims at expanding policy makers’ scope of analysis and providing an auxiliary tool to assess energy planning scenarios in Brazil both dynamically and spatially. A case study for wind power plants in Brazil was performed and the results highlight the unbalance between economic benefits and negative health effects across the wealthiest and poorest regions in the country.

Tags: Regional Economics, Input-Output

  • 5. Tracking an Atmospheric River in a Warmer Climate: from Water Vapor to Economic Impacts 

(revise and resubmit to Earth System Dynamics)

Francina Dominguez, Sandy Dall’erba, Shuyi Huang, Andre F. T. Avelino, Ali Mehran, Huancui Hu, Arthur Schmidt, Lawrence Schick and Dennis Lettenmaier

Abstract: Atmospheric rivers (ARs) account for more than 75% of heavy precipitation events and nearly all of the extreme flooding events along the Olympic Mountains and western Cascade mountains of western Washington state. In a warmer climate, ARs in this region are projected to become more frequent and intense, primarily due to increases in atmospheric water vapor. However, it is unclear how the changes in water vapor transport will affect regional flooding and associated economic impacts. In this work, we present an integrated modeling system to quantify the atmospheric-hydrologic-hydraulic and economic impacts of the December 2007 AR event that impacted the Chehalis river basin in western Washington. We use the modeling system to project impacts under a hypothetical scenario where the same December 2007 event occurs in a warmer climate. This method allows us to incorporate different types of uncertainty including: a) alternative future radiative forcings, b) different responses of the climate system to future radiative forcings and c) different responses of the surface hydrologic system. In the warming scenario, AR integrated vapor transport increases, however, these changes do not translate into generalized increases in precipitation throughout the basin. The changes in precipitation translate into spatially heterogeneous changes in sub-basin runoff and increased streamflow along the entire Chehalis main stem. Economic losses due to stock damages increased moderately, but losses in terms of business interruption were significant. Our integrated modeling tool provides communities in the Chehalis region with a range of possible future physical and economic impacts associated with AR flooding.

Tags: Regional Economics, Flood, Input-Output

Research in Progress

  • 1. Following the Buck: Externalities of American Households in an Evolving Trading World

Andre F. T. AvelinoAndre Carrascal Incera and Alberto Franco Solís

Abstract: The growing fragmentation of production processes and expansion of international trade in the last decades have increase the scope and complexity of value added chains worldwide causing a significant rearrangement of sectoral linkages intra and interregionally. In terms of economic spillovers, this implies that a dollar entering a particular economy follows a different path than before, permeating in longer interregional feedback loops and creating additional multiplier effects outside its origin. However, it also implies that the environmental burden that such dollar embeds has changed in scale and spatial distribution. In this paper, we explore the evolution of these “paths” during 1997-2009 and highlight the main drivers of observed structural change that contribute to the surge or decline of economic spillovers and greenhouse gases emissions spatially. We specifically study the effects of an increase in income in the United States, the country with the largest trade volume in the world. We take advantage of the Extended Temporal Leontief Inverse framework, that allows tracing the evolutionary path of the American households’ multiplier in a dynamic fashion, isolating the contribution of expenditure patterns, income, trade and foreign structural change to the temporal evolution. We find similar growing multiplier effects inside and outside the US due to services and manufacturing respectively, but a declining local environmental burden due to changes in interindustrial relations inside the US with declining manufacturing. We also highlight the fragmentation process with declining foreign intraregional spillovers and increasing trade spillovers. Finally, structural and trade pattern changes in the EU-15 have induced larger spillovers from US consumption to the region with lower environmental impact while disproportionally increasing pollution in developing nations.

Tags: Temporal Leontief Inverse, Time-series Analysis, Trade, Dynamics

  • 2. Now Hiring: Seasonal Labor Requirements through a Quarterly I-O model

Andre Carrascal Incera, Andre F. T. AvelinoAlberto Franco Solís and Diana Gutierrez Posada

Abstract: After almost a decade of economic recession, unemployment rates have started to decrease across nations, and growth has slowly resumed. Nonetheless, the recovery in Spain has been slower and the composition of jobs has changed significantly from the pre-crisis period, with a higher share of temporary contracts. This has translated into increased variability in the employed-unemployed condition of the labor force along the year, which ultimately impacts seasonal final demand. Despite capturing economy-wide effects, current Input-Output models are still limited in their assessment of intra-year shocks because they are based on annual accounts. Hence, traditional employment multipliers per se offer little insight into these issues. Moreover, although demo-economic models introduce different labor statuses and consumption profiles, they also have an annual basis. In sum, intra-year seasonality in labor requirements has been largely ignored in the Input-Output framework, relying on a temporal aggregation that prevents capturing such employment movements. This topic is particularly important for impact assessments, especially in the case of those sectors involving seasonal production, such as some primary and services activities. Therefore, the aim of this paper is to introduce an Input-Output framework that merges intra-year tables and a cost-share model of employment requirements that yields jobs by contract duration and quarters, and inter-temporal production levels. This model follows the T-EURO method proposed by Avelino (2017) and an econometrically estimated translog cost function in line with Kim and Hewings (2015). This paper uses data from the World Input-Output Database and the Continuous Sample of Employment Histories for Spain to illustrate its application.

Tags: Labor market, Econometric Input-Output, Seasonality