Sources of Variation in Economic Impact Multipliers

Abstract

The conceptual arguments and empirical analyses in the article illustrate that when tourism organizations replicate economic impact analyses and/or compare their results with those reported by others, perceived differences often are specious because they are attributable to artifacts in multiplier measurement as well as to changes in the structure of host economies. Four sources of variation in multipliers that may result in specious comparisons are addressed: differences in specifications of the three main types of models used in economic impact analyses, semantic and definition confusion, changes in communities' economic structures, and calibration and decision rule changes.

Untitled

“…It is important to highlight that a correct quantification in impact studies requires a careful methodology. Research published by authors like Crompton et al (2016), Davies et al (2013), Matheson (2006) and Crompton (2006 and1995) insist on rigor in terms of data collection and the application of statistical tools, to avoid common mistakes. Researchers and experts define the existence of different methods to measure the economic impact, among which they mention four: satellite accounts, input-output tables, the Computable General Equilibrium (CGE) model and Cost-Benefit Analysis (CBA).…”

Measuring the economic contribution of beer festivals on local economies: The case of York, United Kingdom

“…Several empirical studies in the tourism literature address the economic contribution and impact of event tourism by quantifying and measuring the total expenditure associated with gated events and festivals. Some of these studies differentiate between impacts generated by expenditure generated by resident and non‐resident visitors, or between levels of local and non‐local custom for local businesses, to identify “deadweight” expenditure, thus local expenditure generated regardless of the presence of the given event or occurrence (Crompton, Lee, & Shuster, 2001; Crompton, Jeong, & Dudensing, 2016). Usually, deadweight expenditure is considered to be “switched spending, which offers no net economic stimulus to the town (…) Hence, this money should not be included when estimating economic impact” (Crompton et al,2001, p. 81).…”

“…Other studies calculate total expenditure as the sum of direct and indirect effects: direct effects occur when there is an increase in the final use for a particular industry output, whereas indirect effects address the impact that the induced stimulus has on the industry of reference through its supply chain (Bracalente et al, 2011; C. Lee et al, 2013). Direct and indirect effects associated with expenditure on goods and/or services at a given event can be captured by using Type I multipliers, thus multiplier ratios constructed from input–output tables constructed for each industry (Crompton et al, 2016). Examples of multiplier ratios include GVA effects, which measure the value of a given output minus the value of its intermediate consumption; and employment effects, which consider the number of full‐time equivalent (FTE) jobs created for every £1 million of total output produced in a given industry or sector of activities (ONS, 2018).…”

“…To our knowledge, this is the first empirical analysis addressing the economic effects generated by a beer tourism‐related event, which explores these effects in such a deep level of granularity. The methodology we apply to our large sample is based on previous methods (Bracalente et al, 2011; Crompton, Jeong, & Dudensing, 2016; Crompton, Lee, & Shuster, 2001; C. Lee, Lee, & Yoon, 2013) but shows significant potential in terms of stimulating the debate among researchers and in view of creating new venues for future research, particularly with regard to measuring the impact generated by festivals and events on local economies. In addition, our study responds to calls from craft brewing scholars for studies addressing the impact of small and craft breweries within regional and local economies (Danson et al, 2015) and about the strategic role that tourism practices can play in the continued development of the beer brewing sector (Dunn & Wickham, 2014).…”

Linkage analysis of tourism‐related sectors in China: An assessment based on network analysis technique

“…Additionally, some scholars have used extended I‐O models, such as SAM (Akkemik, ; Bhatt & Munjal, ; Oosterhaven & Fan, ), CGE (Banerjee et al, ; Blake, Sinclair, & Sugiyarto, ; Dwyer et al, ), and TSA (Frechtling, ; Kenneally & Jakee, ; Sharma & Olsen, ), to evaluate the linkages and impacts of tourism on an economy. However, these extended methods have high requirements for data, and the applications of these methods are very complicated (Crompton, Jeong, & Dudensing, ).…”