Purpose – The purpose of this paper is to improve the forecast of tourism inflows into Spain by use of Google – indices on internet searches measuring the relative popularity of keywords associated with travelling to Spain. Design/methodology/approach – Two models are estimated for each of the three countries with the largest tourist flows into Spain (Germany, UK and France): a conventional model, the best ARIMA model estimated by TRAMO (model 0) and a model augmented with the Google-index relating to searches made from each country (model 1). The overall performance of both models is compared. Findings – The improvement in forecasting provided by the short-term models that include the G-indicator is quite substantial up to 2012, reducing out of sample mean square errors by 42 per cent, although their performance worsens in the following years. Research limitations/implications – Deeper study and conceptualization of sources of error in Google trends and data quality is necessary. Originality/value – The paper illustrates that while this new tool can be a powerful instrument for policy makers as a valuable and timely complement for traditional statistics, further research and better access to data is needed to better understand how internet consumers’ search activities translate (or not) into actual economic outcomes.
This paper reviews some of the applications that use the vast swathes of information provided by Internet user searches for economic analysis and forecasting. This enormous volume of information, available in real time, can be handled by analysts thanks to statistical tools such as "Google Insights for Search", which allow trends in different areas of interest to be classified and evaluated. Previous work focused predominantly on the labour market, on the housing market, on retail sales and on consumer confidence. This paper presents a very specific application for the Spanish economy: British tourist inflows to Spain (the Spanish tourist industry's main customers). The improvement in the forecasting provided by the short-term models that include the G-indicator depends on the benchmark model. This does, however, allow an adjusted indicator of the inflow of British tourists to be obtained with a lead of almost one month. This is but an initial step in the use of on-line searches for constructing leading indicators of economic activity. Other applications to be explored are car sales, consumer confidence and house purchases. The chief characteristic of these procedures is that, with time and the continuous growth of Internet use, results can only improve in the future. It should nonetheless be recalled that the construction of these G-indicators requires caution so as to avoid mistakes arising, inter alia, from the different use of language in different countries. Not taking due caution and blindly confiding in these indicators may lead to erroneous results being obtained.
This paper reviews some of the applications that use the vast swathes of information provided by Internet user searches for economic analysis and forecasting. This enormous volume of information, available in real time, can be handled by analysts thanks to statistical tools such as "Google Insights for Search", which allow trends in different areas of interest to be classified and evaluated. Previous work focused predominantly on the labour market, on the housing market, on retail sales and on consumer confidence. This paper presents a very specific application for the Spanish economy: British tourist inflows to Spain (the Spanish tourist industry's main customers). The improvement in the forecasting provided by the short-term models that include the G-indicator depends on the benchmark model. This does, however, allow an adjusted indicator of the inflow of British tourists to be obtained with a lead of almost one month. This is but an initial step in the use of on-line searches for constructing leading indicators of economic activity. Other applications to be explored are car sales, consumer confidence and house purchases. The chief characteristic of these procedures is that, with time and the continuous growth of Internet use, results can only improve in the future. It should nonetheless be recalled that the construction of these G-indicators requires caution so as to avoid mistakes arising, inter alia, from the different use of language in different countries. Not taking due caution and blindly confiding in these indicators may lead to erroneous results being obtained.
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