Recipient Organization
UNIV OF IDAHO
875 PERIMETER DRIVE
MOSCOW,ID 83844-9803
Performing Department
(N/A)
Non Technical Summary
The goal of this project is to develop a transparent, open-access virtual laboratory (Tapestry) providing an array of in-situ data and analytic services that enables researchers, extension professionals, and policy makers to investigate inter-regional, inter-temporal, and inter-sectoral relationships at county-level regional economies of the United States. Open-access to comprehensive, inter-temporal and detailed multiregional social accounts (MR-SAM) of domestic US regional economies, and the methods used to derive MR-SAM, are not available to researchers and practitioners in a collaborative, transparent manner. The lack access to fine spatial granularity in social accounts is hindering the understanding of economic growth, recovery, and income distribution across a spatially disparate nation. Enabling experiments and applications with replicable sets of cross-sectional and time-series accounts and general equilibrium models, allows new insights into the causes and nature of income growth across the nation, differences in income distribution across the nation, differences in wealth distribution across the nation, and measures of the economic interdependency of different regions. Additional examples of the types of analysis that these accounts will make possible include a more detailed and customized understanding of how forest and agricultural sectors contribute to regional economies in terms of both economic growth and resiliency, the impacts of different federal and state policies on agricultural and natural resource sectors, the development of inter-disciplinary, integrated economic-hazard/disaster impact and recovery models, the reconciliation of regional economic redevelopment and national economic development efforts, clearer understanding of the underlying relationships between current account activity and the accumulation of wealth and capital, and the ability to address regional and national economic growth, distribution, and trade policy which explicitly accounts for geographic differences across the nation.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
The goal of this project is to develop a transparent, open-access virtual laboratory (Tapestry) providing an array of in-situ data and analytic services, primarily in the form of Multi-Regional Social Accounting Matrices (MR-SAMs), that enables researchers, extension professionals, and policy makers to investigate at fine geographical resolution the inter-regional, inter-temporal, and inter-sectoral relationships that exist in county-level regional economies of the United States. Open-access to comprehensive, inter-temporal and detailed MR-SAMs of domestic US regional economies, and the methods used to derive them, have never been available to researchers and practitioners in a collaborative, open-access and transparent manner. The lack access to fine spatial granularity in social accounts is hindering our ability to understand economic growth, recovery, and income distribution across a spatially disparate nation. By enabling experiments and applications with replicable sets of cross-sectional and time-series accounts and general equilibrium models, this laboratory will allow new insights into the causes and nature of income growth across the nation, differences in income distribution across the nation, differences in wealth distribution across the nation, and measures of the economic interdependency of different regions on each other. Additional examples of the types of analysis that these accounts will make possible are the development of inter-disciplinary, integrated economic-hazard/disaster impact and recovery models, deep understanding of how forestry, agricultural and natural resource industry clusters contribute to the growth and resiliency of regional economies, the reconciliation of regional economic redevelopment and national economic development efforts, clearer understanding of the underlying relationships between current account activity and the accumulation of wealth and capital, and the ability to address regional and national economic growth, distribution, and trade policy which explicitly accounts for geographic differences across the nation. The goal of this project is to develop a transparent, open-access virtual laboratory (Tapestry) providing an array of in-situ data and analytic services, primarily in the form of Multi-Regional Social Accounting Matrices (MR-SAMs), that enables researchers, extension professionals, and policy makers to investigate at fine geographical resolution the inter-regional, inter-temporal, and inter-sectoral relationships that exist in county-level regional economies of the United States. Open-access to comprehensive, inter-temporal and detailed MR-SAMs of domestic US regional economies, and the methods used to derive them, have never been available to researchers and practitioners in a collaborative, open-access and transparent manner. The lack access to fine spatial granularity in social accounts is hindering our ability to understand economic growth, recovery, and income distribution across a spatially disparate nation. By enabling experiments and applications with replicable sets of cross-sectional and time-series accounts and general equilibrium models, this laboratory will allow new insights into the causes and nature of income growth across the nation, differences in income distribution across the nation, differences in wealth distribution across the nation, and measures of the economic interdependency of different regions on each other. Additional examples of the types of analysis that these accounts will make possible are the development of inter-disciplinary, integrated economic-hazard/disaster impact and recovery models, deep understanding of how forestry, agricultural and natural resource industry clusters contribute to the growth and resiliency of regional economies, the reconciliation of regional economic redevelopment and national economic development efforts, clearer understanding of the underlying relationships between current account activity and the accumulation of wealth and capital, and the ability to address regional and national economic growth, distribution, and trade policy which explicitly accounts for geographic differences across the nation.
Project Methods
Social AccountsSocial accounts are a set of data elements that track the monetary flows between industries and institutions within a region. A specific set of social accounts for the United States at the national level are the National Income and Product Accounts (NIPA). NIPA are a comprehensive set of the economic transactions that take place in the national economy (Landefeld 2000). Prior to the development these accounts, little quantitative or systematic information was available for understanding the function and health the national economy. Credit for developing a systematic set of accounts is given to Nobel Laureates Richard Stone in the United Kingdom and Simon Kuznets in the United States. Dr. Kuznets reported the first set of national accounts to congress in 1937 and they have been at the core of U.S. economic analysis and policy ever since.In fact, Dr. Michael Boskin, former chair of the council of economic advisors has stated that, without the national income and product accounts, the U.S. would be stuck in an economic dark age (Landefeld 2000). Furthermore, Senator Paul Sarbanes, former ranking member on the Committee on Banking, Housing and Urban Affairs, states "The GDP accounts provide Congress and the rest of government with vital signs on our economy's health. We are making better economic policy today because the GDP accounts give us a better understanding of what policies work. We should devote more resources for modernizing the GDP accounts to keep our statistical infrastructure in step with our rapidly evolving economy." Krueger et al. (2007) called NIPA "arguably the foremost contribution of economics in the last century".A social accounting matrix (SAM) is essentially an integration of I-O accounts and income and product accounts. As Barnard (1967) notes, the concepts underlying flow-of-funds accounts, balance-of-payments statements, and national balance sheets are also integrated into a SAM. The essential features of the SAM is that it is defined and drawn up in such a way that connections between the various transactors of the economy can be traced. The SAM is designed for the specific analytical purpose of measuring the flows of goods and services among the various transactors within a region and between other regions. It embodies treatment of production in which several different classifications, each of which is appropriate to a particular part of the economy, are reconciled. In addition, investment - by producing industries, consumers' durable goods, and governments' social capital - is included. Also, the financial transactions among the various sectors of the economy are recorded, as well as those occurring in aggregate between resident institutions. SAMs make use of classification converters, which provide a means of looking at the sectors of the economy in the various roles they play in production, consumption, accumulation, and trade. Stone (1961) points out that classification converters provide an added dimension to a social accounting system - in particular that it enables us to deal with problems in their own context and to be quite open about the complexities of the real world that lead us to want several classifications.More recently, in response to the Great Recession of December 2007 - 2009 (BLS 2012), the United States again finds itself needing more detailed and sophisticated economic data to help understand the effects of the recession and how to recover from it. Specifically, the lack of regionally specific income and product data hampers our ability to understand how to recover across a spatially disparate nation. The Great Recession, while broad based, exhibited great variation across geographies. Nobel Lauriat Paul Krugman, among others, has voiced the need to look more closely at regional differences in economic data to more finely tune economic policy (Krugman 1991,, Fujita et al. 1999, Combes et al. 2008). Additionally, new insights from economic geography highlight the need to account for the interconnections between regions and the associated spatial interdependencies that arise.Interregional Trade AccountsExogenous final demand within a social accounting model for a sub-region is different than that for the region as a whole. This difference relates primarily to inter-regional trade that is outside the region at the regional level but inside at the higher level of regional aggregation. This outside-inside the region final demand distinction makes aggregating regional results to the national level problematic. A solution to this problem lies in a derivation of a multi-regional input-output model (Round, 1985).For example, a consolidated region with three inter-related sub-regions can be modeled by separating the export-import-transfer flows between them from their respective totals (see Figure 1). By so doing, each sub-region becomes an exogenous institution to the other sub-region with a column vector of exports & transfers and a row vector of imports and transfers to the other. At the same time this inter-sub-regional trade and transfers are endogenous to the consolidated region. We would expect three effects from a consolidated bi-regional model: those contained within each sub-region, those that feedback in a loop between regions and those that spillover (without feedback) from one to the other.Defourny and Thorbecke (1984) assert that embedded within each element of the inter-industry transactions matrix there exists an implicit set of supply chains connecting the flow of products and by-products from a sector of origin to a sector of destination. The challenge is to make these implicit supply chains explicit. To do this, they used a technique called structural path analysis and thereby proved their assertion. This technique uses a disaggregated cofactor element in an adjoint I-A matrix to determine the number and size of direct paths and path multipliers, for example, from agricultural production to food and fiber products for households.Koks et al. used a hybrid (linear and non-linear) multi-regional input-output model of Europe to estimate the continent-wide impacts of simulated floods in the Netherlands. Their results show that most regions are unaffected by the flood disaster. Those outside regions that are affected include those that benefit from increased demand for output for substitutes and constructions while those that suffer losses are the result of supply chain disruption. The net effect of these gains and losses depends on the size of the initial disaster. The indirect effects are positive for small disasters and negative for large ones.