Timely data availability is a long-standing challenge in policy-making and analysis for low-income developing countries. This paper explores the use of Google Trends’ data to narrow such information gaps and finds that online search frequencies about a country significantly correlate with macroeconomic variables (e.g., real GDP, inflation, capital flows), conditional on other covariates. The correlation with real GDP is stronger than that of nighttime lights, whereas the opposite is found for emerging market economies. The search frequencies also improve out-of-sample forecasting performance albeit slightly, demonstrating their potential to facilitate timely assessments of economic conditions in low-income developing countries.
Mr. Futoshi Narita, Rujun Yin, Mr. Ali M. Mansoor, and Mr. Chris Papageorgiou
data obtained through recent technology have enormous potential to fill information gaps in developing economies. We investigate how much information we could obtain from Internet search frequencies to strengthen the capacity to monitor and assess current economic developments.
Our findings help us better utilize new sources of information such as GoogleTrends’ data in economic analyses . Useful information contained in Google’s SVI is demonstrated by the improved in-sample and out-of-sample performances of a simple forecasting model, conditional on lagged
the predictive ability of GoogleTrendsdata for tourist arrivals to The Bahamas . With the spread of the Internet throughout the world, the data collected by search engines like Google allows researchers to measure the intended behavior of consumers at the individual level and take that into account in forecasting at the macroeconomic level. Furthermore, the availability of internet search data provides new high-frequency information that can potentially improve forecast accuracy. Accordingly, this paper develops an econometric model of tourist arrivals to The
The widespread availability of internet search data is a new source of high-frequency information that can potentially improve the precision of macroeconomic forecasting, especially in areas with data constraints. This paper investigates whether travel-related online search queries enhance accuracy in the forecasting of tourist arrivals to The Bahamas from the U.S. The results indicate that the forecast model incorporating internet search data provides additional information about tourist flows over a univariate approach using the traditional autoregressive integrated moving average (ARIMA) model and multivariate models with macroeconomic indicators. The Google Trends-augmented model improves predictability of tourist arrivals by about 30 percent compared to the benchmark ARIMA model and more than 20 percent compared to the model extended only with income and relative prices.
. , and G. Jenkins , 1976 , Time Series Analysis: Forecasting and Control ( San Francisco : Holden-Day )
Carrière-Swallow , Y. , and F. Labbé , 2013 , “ Nowcasting with Google Trends in an Emerging Market , Journal of Forecasting , Vol. 32 , pp. 289 – 298 . 10.1002/for.1252
Chen , T. , E. So , L. Wu , and I. Yan , 2015 , “ The 2007–2008 U.S. Recession: What Did the Real-Time GoogleTrendsData Tell? ” Contemporary Economic Policy , Vol. 33 , pp. 395 – 403 .
Choi , H. , and H. Varian , 2009 , “ Predicting
International Monetary Fund. Western Hemisphere Dept.
words “Panama City apartments” and “Panama City houses”, based on GoogleTrendsdata (in percent change, Y/Y)
α i = Constant
ε i = Residuals
Residential Property Price-to-Income Ratio
Real GDP Growth
IMF World Economic Outlook
United Nations (World Population Prospects 2019)
Superintendency of Banks
2 . Model 1(a) is derived mainly on fundamental variables . The explanatory variables comprise real
Cornelia L. Hammer, Diane C. Kostroch, Gabriel Quirós, and Louis Marc Ducharme
concept development: (1) Using SWIFT data to monitor global financial flows, (2) a sentiment-based early-warning system, (3) nowcasting GDP using Googletrendsdata, (4) automating and expanding the Week @ the Beach Index, (5) pooling government cash flow data to enhance surveillance and policy analysis, and (6) applying analytics for better tax and customs administration. Other examples are the use of big administrative data for the IMF Fiscal Affairs Department Revenue Administration Gap Analysis Program to determine the value-added tax compliance gap and the IMF
Mr. Philip Barrett, Mariia Bondar, Sophia Chen, Miss Mali Chivakul, and Ms. Deniz O Igan
GoogleTrendsdata to identify social unrest events. Although social media coverage may be useful in specific cases, it is near-impossible to separate true unrest-related information from disinformation generated by “trolls”, bots, and the like in a broader sample.
4 In Section 4 we adjust day 0 for the timing difference between the event occurrence and the filing of the news article, given difference in time zones. Getting the timing right is important because we use local stock market data. For example, if a matching article filed in New York references an
International Monetary Fund. Western Hemisphere Dept.
This Selected Issues paper focuses on background, challenges, and policy options in Panama. Panama stands at a crossroad between taking the leap to become an advanced economy or getting stuck in the middle-income trap. The beginning of a new administration provides a window of opportunity to initiate and implement ambitious reforms. This note takes stock of fiscal issues in Panama and proposes policy options. The new administration’s fiscal agenda should feature a comprehensive reform of tax and customs administrations, a review of tax incentives and exemptions and consider steps toward a broader tax policy reform. Efforts to further strengthen the fiscal framework with the appointment of the members of the Fiscal Council should continue going forward. Panama should adopt best practice fiscal accounting and reporting methods. A comprehensive assessment and management of fiscal risks is necessary to create buffers and safeguard public finances given fiscal policy’s exclusive stabilization role.