GSV
trendEcon Austria
This dashboard is based on the work of trendEcon. The data are scraped from Google Trends through the use of the trendecon R-package. The sectoral indicators are slightly adapted to match Austrian search keywords (e.g. different stores). The main focus of this project is to test the accuracy of the main indicator (PES) in a VAR forecasting framework.
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Perceived Economic Situation
Info
Description
The indicator for Perceived Economic Situation includes search terms that reflect people’s worries about the economy. For instance, people then google “economic crisis” (Wirtschaftskrise).
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Clothing and Shoes
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Description
The category Clothing and Shoes includes clothing and shoe stores as well as a general search terms related to buying clothes and shoes. trendEcon found that people directly google for the brands they like. Note: the searchword “zalando” was not included because Zalando was not available in Austria before 2012.
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Home Office
Info
Description
The category Home Office combine Google inquiries related to the new normal of working from home. The working-from-home-index contains the search terms:
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Gardening and Home Improvement
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Description
The category Gardening and Home Improvement includes stores selling materials for home improvement such as building materials, garden accessories and electrical supplies.
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Food Delivery
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Description
The category Food Delivery includes search terms related to take away and ordering pizza.
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Cultural
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Description
The category Cultural Events includes search terms related to concerts, theatres, cinema and ticket providers for such events.
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Travel Abroad
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Description
The category Travel Abroad includes search terms used to book flights and holidays.
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Mobility
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Description
The category Mobility includes search terms related to ground transportation: For instance, checking the railway schedule or calling a taxi.
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Watches and Jewelry
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Description
The category Watches and Jewellery includes stores and brands selling luxurious watches and jewellery goods and related, more general search terms for luxury consumer goods.
moment
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stationärer Handel
Info
Description
The indicator for
VGR Handel - WWWI
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Gastronomie
Info
Description
The indicator for
Keywords
- Oeffnungszeiten
- Bar
- Restaurant
- Mittagsmenu
- Speisekarte
VGR Gastronomie und Beherbergung - WWWI
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Corona Indikator
Zusammensetzung
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Winterurlaub/Skitourismus
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Description
The indicator for
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Elektronik
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Description
The indicator for
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körpernahe Dienstleistungen
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Baumarkt und Garten
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Description
The indicator for
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Einkaufszentren
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Description
The indicator for
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Fitnesscenter
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Description
The indicator for
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Bibliotheken
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Mobilität (Auto)
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Description
The indicator for
PES
The main indicator shows co-movement with the consumer confidence and with the quarterly GDP growth rate. However, in contrast to the trendEcon results for Germany and Switzerland, the main indicator as well as the consumer confidence insufficiently capture the impact of the World Financial Crisis on GDP in the years after 2008/09.
Weekly Indicators
VAR
Results
Vector Autoregressive Model with 12 lags: \(\mathbf{x_t^{AT}} = [ PES_t^{AT}, u_t^{AT}, cpi_t^{AT}]\)
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dependent variables: pes, une, cpi |
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| pes | une | cpi | |
| (1) | (2) | (3) | |
| pest-1 | 0.457*** | -0.187*** | -0.126*** |
| (0.091) | (0.041) | (0.047) | |
|
Δ unet-1 |
-0.062 | 0.560*** | -0.066 |
| (0.200) | (0.089) | (0.102) | |
| cpit-1 | -0.462** | 0.031 | 1.067*** |
| (0.180) | (0.080) | (0.092) | |
| pest-2 | -0.113 | -0.183*** | 0.098* |
| (0.110) | (0.049) | (0.056) | |
|
Δ unet-2 |
-0.108 | 0.208** | -0.070 |
| (0.227) | (0.101) | (0.116) | |
| cpit-2 | 0.518* | -0.069 | -0.144 |
| (0.269) | (0.120) | (0.138) | |
| pest-3 | 0.145 | -0.108** | -0.095 |
| (0.116) | (0.052) | (0.059) | |
|
Δ unet-3 |
-0.028 | -0.067 | -0.083 |
| (0.229) | (0.102) | (0.117) | |
| cpit-3 | -0.278 | -0.001 | 0.131 |
| (0.274) | (0.122) | (0.140) | |
| pest-4 | -0.104 | 0.075 | -0.077 |
| (0.119) | (0.053) | (0.061) | |
|
Δ unet-4 |
0.497** | 0.112 | 0.105 |
| (0.229) | (0.102) | (0.117) | |
| cpit-4 | 0.421 | 0.001 | -0.154 |
| (0.274) | (0.122) | (0.140) | |
| pest-5 | 0.039 | 0.050 | -0.087 |
| (0.119) | (0.053) | (0.061) | |
|
Δ unet-5 |
-0.291 | -0.092 | -0.086 |
| (0.236) | (0.105) | (0.121) | |
| cpit-5 | -0.056 | -0.002 | 0.109 |
| (0.266) | (0.119) | (0.136) | |
| pest-6 | 0.086 | -0.016 | 0.099 |
| (0.118) | (0.053) | (0.061) | |
|
Δ unet-6 |
0.294 | 0.182* | 0.144 |
| (0.236) | (0.105) | (0.121) | |
| cpit-6 | 0.147 | -0.051 | -0.189 |
| (0.228) | (0.102) | (0.117) | |
| pest-7 | 0.134 | 0.026 | 0.267*** |
| (0.116) | (0.052) | (0.059) | |
|
Ε unet-7 |
-0.256 | 0.027 | -0.096 |
| (0.236) | (0.105) | (0.121) | |
| cpit-7 | -0.363* | 0.121 | 0.219** |
| (0.215) | (0.096) | (0.110) | |
| pest-8 | 0.150 | 0.028 | -0.129** |
| (0.126) | (0.056) | (0.064) | |
|
Ζ unet-8 |
-0.070 | 0.133 | 0.098 |
| (0.234) | (0.104) | (0.120) | |
| cpit-8 | 0.176 | 0.014 | -0.276** |
| (0.221) | (0.099) | (0.113) | |
| pest-9 | -0.056 | -0.001 | -0.066 |
| (0.125) | (0.056) | (0.064) | |
|
Η unet-9 |
0.592** | 0.018 | 0.014 |
| (0.233) | (0.104) | (0.119) | |
| cpit-9 | -0.062 | 0.012 | 0.095 |
| (0.227) | (0.101) | (0.116) | |
| pest-10 | 0.124 | -0.053 | -0.023 |
| (0.127) | (0.057) | (0.065) | |
|
⎖ unet-10 |
-0.161 | -0.008 | -0.035 |
| (0.232) | (0.103) | (0.119) | |
| cpit-10 | 0.021 | 0.067 | -0.102 |
| (0.259) | (0.115) | (0.132) | |
| pest-11 | -0.050 | 0.139** | -0.039 |
| (0.129) | (0.057) | (0.066) | |
|
⎖ unet-11 |
-0.098 | -0.042 | 0.010 |
| (0.225) | (0.100) | (0.115) | |
| cpit-11 | -0.105 | -0.204* | 0.272** |
| (0.268) | (0.119) | (0.137) | |
| pest-12 | -0.052 | 0.024 | -0.027 |
| (0.124) | (0.055) | (0.064) | |
|
⎖ unet-12 |
-0.090 | -0.027 | 0.012 |
| (0.188) | (0.084) | (0.096) | |
| cpit-12 | 0.123 | 0.159* | -0.146 |
| (0.186) | (0.083) | (0.095) | |
| constant | -1.377* | -0.153 | 0.525 |
| (0.805) | (0.359) | (0.412) | |
| Observations | 163 | 163 | 163 |
| R2 | 0.396 | 0.910 | 0.928 |
| Adjusted R2 | 0.223 | 0.884 | 0.907 |
| Residual Std. Error (df = 126) | 0.562 | 0.251 | 0.288 |
| F Statistic (df = 36; 126) | 2.295*** | 35.207*** | 44.805*** |
| Note: | p<0.1; p<0.05; p<0.01 | ||
Summary
Data
pes - Perceived Economic Situation (Nowcasting proxy for GDP)
une - Unemployment rate
cpi - Inflation rate year-on-year
all variables are on a monthly frequency
Model diagnostics - residuals
(p.value threshold = 0.05)
multivariate test for serially correlated errors (Portmanteau- and Breusch-Godfrey): H0 of no serial correlation: accepted. p = 0.47
multivariate Jarque-Bera tests:
H0 of Normality: rejected. p = 0
H0 of Skewness = 0: rejected. p = 0
H0 of Kurtosis (excess curtosis = 0): rejected. p = 0
multivariate ARCH-LM test:
H0 of homoskedasticity: accepted. p = 0.18
Model stability - structural breaks
The data lies between the confidence level boundaries and therefore indicates that there are no structural changes in the data.
Sources
PES - scraped from Google Trends using the trendecon r package.
unemployment - Source: Statistik Austria
consumer price index - Source: Statistik Austria
consumer confidence index - Source: OeNB
gdp - Source: OECD
R-Packages: dygraphs, flexdashboard, htmlwidgets, knitr, tsbox, tidyverse, vars, ggplot2, plotly ggfortify, stargazer, forecast
Forecasting
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In sample VAR(12) Forecasting (3M ahead)
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Accuracy
Evaluation of in-sample forecast accuracy (3M ahead)
| var | model | ME | RMSE | MAE | MPE | MAPE |
|---|---|---|---|---|---|---|
| pes | PES | -1.663 | 1.667 | 1.663 | 176.023 | 2854.585 |
| une | PES | 4.763 | 4.766 | 4.763 | 74.715 | 74.715 |
| cpi | PES | 0.549 | 0.817 | 0.601 | 20.739 | 23.859 |
Benchmarks
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Benchmark models (3M ahead)
