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Publication Date:
15 Nov 2017
eISBN:
9781484328903
Language:
English
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Appendix A. Overview of EPU Sample

Table A.1 provides more detailed information on the EPU data. For each country, we list the period for which the series are available and the number of newspapers used by Baker et al. (2016) to construct the EPU index.

Table A.1:

EPU Sample

article image
Source: www.policyuncertainty.com.

Appendix B. Data Sources and Country Groups

Table B.1 provides an overview of the variables used in the empirical analysis, along with the sources and scales.

Table B.1:

Data Sources

article image

Table B.2 lists the countries in our dataset by region. We group countries according to the IMF regional departments.

Table B.2:

List of Countries by Region

article image
*

The views expressed in this Working Paper are those of the authors and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the authors and are published to elicit comments and to encourage debate. We thank, without implicating, Lisandro Abrego, Sergei Antoshin, Ashok Vir Bhatia, Pelin Berkman, Rodrigo Cubero, Alfredo Cuevas, Shilei Fan, Davide Furceri, Florence Jaumotte, Daniel Leigh, Troy Matheson, Carola Moreno, Luca Ricci, Antonio Spilimbergo, Esteban Vesperoni and the participants of the IMF seminar held in August 2017 for their comments and suggestions.

†

International Monetary Fund, Western Hemisphere Department, nbijanovska@imf.org.

‡

International Monetary Fund, Research Department, fgrigoli@imf.org.

§

The Graduate Institute, martina.hengge@graduateinstitute.ch.

1

The sample includes Australia, Canada, China, the Euro Area, Japan, and the UK.

2

Other studies that develop policy uncertainty indexes based on the frequency of keywords in newspapers are limited in their country or topical coverage. Alexopoulos and Cohen (2015) focus only on the US and rely on one newspaper only while Husted et al. (2016) measure uncertainty exclusively about monetary policy.

3

The index captures uncertainty regarding who will make the economic policy decision, when, and what the effect would be as a result of the action.

4

Despite its widespread use in the literature, the EPU index remains potentially subject to measurement error. This may arise, for example, from unequal media coverage across journals and countries, subjective interpretation of the facts, and different writing styles.

5

For the US, Baker et al. (2016) construct an additional index that combines uncertainty derived from newspaper coverage with a measure of the level of uncertainty stemming from federal tax code provisions, and a measure of dispersion of survey-based forecasts by The Philadelphia Federal Reserve. However, to ensure comparability across countries, we use the purely newspaper-based EPU index for the US.

6

See Appendix B for further details on country groups.

7

European EPU is based on EPU in France, Italy, Germany, Spain, and the UK.

8

Restricting the sample of Asia and Pacific economies to countries with at least three million people yields the expected negative and significant correlation coefficient between real GDP growth and EPU in China.

9

In the rest of the paper, we use the terms “spillovers” and “common effects” interchangeably.

10

The sample correlation between ɛi,t and ɛ¯.,t corresponds to OLS estimates of Λi in equation (2) since the variances of ɛi,t and ɛ¯.,t have been normalized to unity (Pedroni, 2013).

11

We ensure that the data on EPU and the year-on-year growth rates of real GDP, private consumption, and private investment are stationary.

12

The finding that spillovers are quantitatively important is in line with other studies, which show that spillovers from general uncertainty in the US are large and similar in magnitude to domestic effects (among others, Colombo, 2016; Kamber et al., 2013; Mumtaz and Theodoridis, 2015).

13

This specification is similar to IMF (2013). Similarly, we do not include year dummies because the variable of interest, EPUj, is common across all countries.

14

One could argue that a better measure of idiosyncratic shocks in the US, Europe, and China is the orthogonal component of each of these countries’ EPU series with respect to the other countries’ ones. This approach, however, would greatly reduce the variation in the series related to idiosyncratic events occurring during the same year. For example, the Eurozone debt crisis and the US debt ceiling discussion, as well as the China leadership transition, took place in 2011; the European immigration crisis and the Chinese equity sell-off happened in 2015; Brexit and the US presidential election occurred in 2016. Despite this drawback, when we use the orthogonal components of the series rather than the original ones, we find that the results for shocks to EPU in the US and China are broadly consistent, and that the results for shocks to European EPU are mixed.

15

We refer to the news-based US EPU index for comparability with the European and Chinese EPU indexes.

16

See, for example, Choi (2017) on the importance of the trade channel in the transmission of EPU shocks.

17

For a more comprehensive discussion on the choice of controls and their link with key macro aggregates, see Grigoli et al. (2014).

18

The low R2 can be explained by the heterogeneity of countries included in our sample. When we restrict the sample to advanced economies, the R2 increases and the coefficients of interest remain similar.

19

This measure is equivalent to the one used in IMF (2013).

20

The results using restricted samples, alternative measures of EPU, and different lag structures are available upon request.

21

The results using the dummy for the GFC, alternative measures of EPU, and different lag structures are available upon request.

22

See Arellano and Bond (1991) and Blundell and Bond (1998) for more details about the S-GMM estimator.

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Cover IMF Working Papers
Fear Thy Neighbor: Spillovers from Economic Policy Uncertainty
Author:
Nina Biljanovska
,
Mr. Francesco Grigoli
, and
Martina Hengge
Volume/Issue:
Volume 2017: Issue 240
Publisher:
International Monetary Fund
ISBN:
9781484328903
ISSN:
1018-5941
Pages:
34
DOI:
https://doi.org/10.5089/9781484325032.001