Heterogeneity in the exchange rate pass-through to consumer prices: the Swiss franc appreciation of 2015

Oktay, Alex

doi:10.1186/s41937-022-00102-7

Swiss Journal of Economics and Statistics

Table 8 Estimates of the exchange rate pass-through to consumer prices for Industrial and Other Goods

From: Heterogeneity in the exchange rate pass-through to consumer prices: the Swiss franc appreciation of 2015

Product category	Pre-trend difference	Standard DID estimate	Synthetic DID estimate	Implied pass-through
All-items HICP	0.01	\(-\)1.64\(^{***}\)	\(-\)1.23\(^{**}\)	0.12
All-items HICP	(0.04)	(0.26)	(0.48)	0.12
Industrial goods (overall index)	\(-\)0.05	\(-\)2.22\(^{***}\)	\(-\)2.02\(^{***}\)	0.2
Industrial goods (overall index)	(0.11)	(0.79)	(0.69)	0.2
Durable industrial goods	0.1\(^{***}\)	\(-\)4.48\(^{***}\)	\(-\)3.62\(^{***}\)	0.36
Durable industrial goods	(0.04)	(0.99)	(0.68)	0.36
Semi-durable industrial goods	\(-\)0.47	1.18	\(-\)0.67	0.07
Semi-durable industrial goods	(0.4)	(1.31)	(1.49)
Audio–visual equipment	0.12\(^{*}\)	\(-\)5.13\(^{***}\)	\(-\)4.92\(^{***}\)	0.49
Audio–visual equipment	(0.06)	(1.9)	(1.36)	0.49
Carpets and other floor coverings	0.14\(^{*}\)	0.75	0.96	\(-\)0.1
Carpets and other floor coverings	(0.08)	(0.5)	(0.95)	\(-\)0.1
Electricity, fuels, and heat energy	\(-\)0.15\(^{**}\)	1.15\(^{***}\)	\(-\)0.82	0.08
Electricity, fuels, and heat energy	(0.08)	(0.37)	(1.25)	0.08
Energy	0.05	\(-\)3.64	\(-\)3.88\(^{**}\)	0.39
Energy	(0.21)	(2.63)	(1.8)	0.39
Transport fuels and lubricants	\(-\)0.15	\(-\)4.57	\(-\)4.03\(^{*}\)	0.4
Transport fuels and lubricants	(0.37)	(3.47)	(2.34)	0.4
Information processing equipment	\(-\)0.18\(^{**}\)	\(-\)1.54	\(-\)1.38	0.14
Information processing equipment	(0.09)	(1.87)	(2.03)	0.14
Liquid fuels	0.51	\(-\)7.18	\(-\)5.13\(^{*}\)	0.51
Liquid fuels	(0.6)	(8.97)	(2.77)	0.51
Maintenance and repair materials	0.25\(^{***}\)	\(-\)1.38\(^{***}\)	0.32	\(-\)0.03
Maintenance and repair materials	(0.07)	(0.16)	(0.53)	\(-\)0.03
Motorcycles and bicycles	\(-\)0.06	\(-\)6.64\(^{***}\)	\(-\)7.29\(^{***}\)	0.72
Motorcycles and bicycles	(0.05)	(0.58)	(1.27)	0.72
Operation of transport equipment	\(-\)0.05	\(-\)3.33\(^{**}\)	\(-\)2.65\(^{*}\)	0.26
Operation of transport equipment	(0.2)	(1.68)	(1.48)	0.26
Purchase of vehicles	0.08\(^{***}\)	\(-\)4.87\(^{***}\)	\(-\)4.68\(^{***}\)	0.46
Purchase of vehicles	(0.01)	(0.89)	(0.78)	0.46
Recreation and culture	0.13	\(-\)4.06\(^{***}\)	\(-\)2.54\(^{***}\)	0.25
Recreation and culture	(0.15)	(0.71)	(0.92)	0.25
Solid fuels	0.39\(^{*}\)	\(-\)6.58\(^{***}\)	\(-\)8.01\(^{***}\)	0.80
Solid fuels	(0.21)	(1.55)	(1.02)	0.80
Miscellaneous goods and services	\(-\)0.12\(^{***}\)	\(-\)0.82\(^{**}\)	\(-\)0.89\(^{**}\)	0.09
Miscellaneous goods and services	(0.02)	(0.34)	(0.37)	0.09

The DID estimates are computed using the Eurostat (2022) HICP consumer price data from January 2014 to December 2015, with Switzerland as the treated unit and 33 European countries as a control group. The treatment time (Swiss franc appreciation) is in January 2015, so that the pre-treatment period is from January to December 2014 and post-treatment from January to December 2015. Standard DID estimates are computed with Eq. 3 using a GDP-weighted control group, and synthetic DID estimates with the Arkhangelsky et al. (2021) method. Pre-trend difference is the difference in slope between two pre-treatment linear regressions for Europe and Switzerland (eq. 1) which should be zero under the pre-trend assumption. The 1-year pass-through is implied from the synthetic DID estimates and is computed using Eq. 4. \(^{*}p<0.1\); \(^{**}p<0.05\); \(^{***}p<0.01\)

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