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Predicting the Present with Search Engine Data
Published on Sep 27, 20136800 Views
Many businesses now have almost real time data available about their operations. This data can be helpful in contemporaneous prediction (“nowcasting”) of various economic indicators. We illustrate how
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Chapter list
Bayesian Variable Selection for Nowcasting Time Series00:00
What day of the week are there the most searches for [hangover]?00:30
Searches for [hangover]01:01
Searches for [hangover] and [vodka]02:05
Looking for gifts when single02:22
Looking for gifts when married02:42
Problem motivation03:08
Example: unemployment06:04
Build a simple AR model07:36
But sometimes simple correlation doesn't work09:32
How to avoid spurious correlation?10:53
Some approaches to variable selection12:09
Our approach12:59
How BSTS helps reduce over14:06
Basic structural model with regression17:10
Intuition for Kalman 20:00
Nice features of Kalman approach22:38
Spike and slab regression for variable choice24:25
Bayesian model averaging26:34
Torture test simulation for BSTS27:17
Example of torture test28:43
Example 1: Consumer Sentiment30:18
Consumer sentiment as leading indicator31:40
Variable selection32:49
UM Consumer Sentiment Predictors33:26
Posterior distribution of one-step ahead forecast35:25
State decomposition35:41
Trend and regression decomposition36:24
Trend37:02
add Investing37:24
add Search Engines37:28
add Financial Planning37:57
add Business News38:06
Example 2: gun sales38:22
Google Correlate Results40:02
Trend40:55
Seasonal41:07
Gun Shops41:17
Google Trends predictors41:53
State decomposition42:54
Trend42:58
Seasonal43:01
Hunting and Shooting43:08
Searches for [gun shop]43:16
Fun with priors44:09
New Homes Sold in the US45:26
Run correlate46:05
BSTS variable selection47:00
Eliminate spurious correlates47:47
State decomposition48:03
Predictors48:16
Trend48:23
Seasonal48:34
Appreciation rate48:39
IRS 103148:41
Century 21 realtors48:44
Real estate appraisal48:47
Estate appraisal48:54
Real estate purchase48:55
80-20 mortgage48:56
Future work48:57