(A)symmetry, (Non)linearity and Hysteresis of Pricing-To-Market: Evidence from German Sugar Confectionery Exports

Svetlana Fedoseeva

doi:10.1515/jafio-2013-0003

Article

(A)symmetry, (Non)linearity and Hysteresis of Pricing-To-Market: Evidence from German Sugar Confectionery Exports

Svetlana Fedoseeva

Published/Copyright: May 22, 2013

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From the journal Journal of Agricultural & Food Industrial Organization Volume 11 Issue 1

Abstract: Pricing-to-market (PTM) is often reported to be adopted by exporters, who have invested in their presence on international markets and are interested in keeping and developing their market shares. Then, a markup adjustment is used to partially offset changes of the exchange rate, which are unfavorable for their foreign customers, in order to keep the price level in the importer’s currency relatively unchanged. With only few exceptions, empirical literature often considers PTM adjustments to be linear and symmetric. If asymmetry is allowed, PTM is often regarded as contemporaneous, which is a very simplifying assumption, given the goals pursued by exporters employing PTM strategies. This paper applies the dynamic autoregressive distributed lag (ADRL) approach popularized by Pesaran, Shin, and Smith (2001) and its nonlinear extension by Shin, Yu, and Greenwood-Nimmo (2011) to the data of German sugar confectionery exports to various destination markets. It turns out that in the long-run PTM is neither linear nor symmetric.

Keywords: pricing-to-market; asymmetric cointegration; nonlinear ARDL model; sugar confectionery

JEL codes: F14; L11; L66

Acknowledgements

I thank Prof. Dr. Azzeddine Azzam, Prof. Dr. Roland Herrmann, Dr. Sebastian Bredl, Heiko Dreyer and anonymous reviewer(s) for helpful comments. Financial support of the German Research Foundation (DFG) through the project “What explains the agricultural trade of the EU and Germany? Theoretical and econometric investigation of liberalization, macro-, and hysteresis effects” is gratefully acknowledged.

Appendix A

Table 10

Static asymmetric regression outcomes. Case 1: T = (P25, 0, P75).

	CAN		SWE		SWI		UK		US
	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS
e_nl	-0.720***	-0.840***	-0.026	-0.036	0.123	0.160	0.065	-0.085	-0.194	-0.407
e_nl	0.277	0.252	0.033	0.031	0.137	0.164	0.236	0.261	0.345	0.268
e_ns	-0.057	-0.450	0.002	-0.007	0.634	0.844	2.265	1.769	0.886	0.401
e_ns	0.567	0.655	0.120	0.163	0.595	0.727	1.538	1.683	1.196	1.099
e_ps	1.025	2.069	0.445	0.332	-0.780	-1.324	-1.639	-1.305	2.199	3.236**
e_ps	1.398	1.491	0.274	0.291	1.169	1.416	1.793	2.051	1.759	1.567
e_pl	-0.406***	-0.342**	0.028	0.020	-0.478**	-0.716**	-0.406**	-0.402*	-0.623*	-0.325
e_pl	0.132	0.163	0.022	0.026	0.224	0.282	0.197	0.253	0.328	0.380
gdph	1.451*	1.468*	-0.642	-0.738	0.292	0.112	-1.174**	-1.176**	0.412	0.063
gdph	0.784	0.754	0.485	0.535	0.335	0.339	0.501	0.571	1.026	1.074
gdpf	-0.270	-0.234	0.033	-0.017	-0.335*	-0.410*	1.681***	1.642***	-0.608	-0.044
gdpf	0.177	0.199	0.130	0.126	0.182	0.239	0.357	0.411	0.875	0.785
mc	2.192***	2.004***	0.654***	0.653***	0.115**	0.151***	0.210***	0.256***	1.736***	1.860***
mc	0.248	0.149	0.174	0.116	0.052	0.049	0.064	0.077	0.268	0.177
Trend	-0.010	-0.016	-0.005	-0.004	0.006	0.009	0.002	0.001	0.006	-0.004
Trend	0.010	0.010	0.004	0.005	0.004	0.005	0.005	0.006	0.015	0.013
Adj.R²	0.667	0.663	0.331	0.327	0.815	0.812	0.332	0.326	0.745	0.742

Notes: 1. OLS – heteroscedasticity robust standard errors reported under the coefficient. 2.FMOLS estimated with standard Eviews7 settings (Long-run covariance estimate (Bartlett kernel, Newey-West fixed bandwidth =5). 3.

^[***]^[**]^[*]

Table 11

Static asymmetric regression outcomes. Case 2: T = (–Std.Dev., 0, +Std.Dev.).

	CAN		SWE		SWI		UK		US
	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS
e_nl	-0.336***	-0.336**	-0.007	-0.031	-0.058	-0.067	-0.277	-0.373**	0.028	-0.087
e_nl	0.132	0.142	0.029	0.027	0.084	0.105	0.152	0.169	0.183	0.162
e_ns	-1.273**	-1.139**	-0.035	-0.094	-0.344	-0.397	0.139	-0.254	-1.282*	-1.405*
e_ns	0.561	0.566	0.100	0.109	0.304	0.424	0.715	0.799	0.767	0.826
e_ps	0.488	0.477	0.206**	0.202*	0.550	0.419	0.066	-0.033	1.361***	1.679**
e_ps	0.558	0.614	0.093	0.114	0.501	0.602	0.746	0.789	0.430	0.675
e_pl	-0.159	-0.186	0.044	0.046	-0.212	-0.377	-0.243	-0.364	-0.088	0.115
e_pl	0.122	0.153	0.031	0.030	0.164	0.239	0.194	0.238	0.273	0.359
gdph	1.370	0.922	-0.369	-0.557	0.643***	0.621*	-0.596*	-0.559	0.470	0.327
gdph	0.883	0.986	0.475	0.554	0.213	0.236	0.324	0.413	1.066	1.206
gdpf	1.166	0.871	-0.195	-0.267*	-0.504***	-0.555**	1.424***	1.307**	-1.182	-0.714
gdpf	0.639	0.725	0.152	0.151	0.183	0.255	0.467	0.566	0.891	0.933
mc	2.221***	2.028***	0.668***	0.674***	0.120**	0.162***	0.215***	0.269***	1.815***	2.002***
mc	0.237	0.149	0.174	0.114	0.056	0.051	0.065	0.078	0.277	0.181
Trend	-0.025***	-0.021**	-0.007	-0.009	-0.002	-0.001	-0.004	-0.005	-0.010	-0.017
Trend	0.009	0.009	0.006	0.006	0.003	0.004	0.003	0.003	0.008	0.010
Adj.R²	0.675	0.672	0.332	0.327	0.816	0.813	0.325	0.318	0.742	0.738

Notes: See Table 10.

Table 12

Static asymmetric regression outcomes. Case 3: T = (P10, 0, P = 90).

	CAN		SWE		SWI		UK		US
	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS	OLS	FMOLS
e_nl	-0.180	-0.162	-0.003	-0.025	0.111	0.131*	-0.060	-0.125	-0.550***	0.682***
e_nl	0.132	0.128	0.028	0.024	0.069	0.077	0.131	0.152	0.196	0.234
e_ns	-1.293***	-1.173***	0.026	-0.041	0.654***	0.745***	-0.116	-0.326	0.797**	0.816**
e_ns	0.323	0.251	0.075	0.089	0.198	0.256	0.503	0.532	0.370	0.363
e_ps	0.749***	0.816***	0.148**	0.122	-0.385	-0.688	-1.239**	-1.242*	-0.316	-0.144
e_ps	0.280	0.281	0.069	0.092	0.366	0.465	0.581	0.638	0.440	0.683
e_pl	-0.090	-0.163	0.034	0.033	-0.486***	-0.649***	0.220	0.103	-1.237***	-1.245***
e_pl	0.143	0.169	0.024	0.027	0.131	0.169	0.200	0.243	0.288	0.349
gdph	1.544**	1.361*	-0.375	-0.638	0.656***	0.523***	-0.583*	-0.551	-1.123	-1.382
gdph	0.737	0.725	0.478	0.561	0.175	0.198	0.330	0.411	0.987	1.158
gdpf	2.145***	1.863***	-0.143	-0.206	-0.798***	-0.769***	2.080***	1.974***	0.713	1.273
gdpf	0.624	0.679	0.133	0.145	0.187	0.243	0.395	0.465	0.907	0.978
mc	2.375***	2.264***	0.677***	0.690***	0.066	0.069	0.227***	0.284***	1.638***	1.689***
mc	0.239	0.137	0.174	0.115	0.052	0.047	0.069	0.078	0.277	0.177
Trend	-0.034***	-0.031***	-0.003	-0.005	0.008***	0.010***	-0.005***	-0.006***	0.015**	0.011
Trend	0.008	0.006	0.003	0.004	0.002	0.003	0.003	0.003	0.006	0.008
Adj.R²	0.696	0.694	0.329	0.323	0.822	0.819	0.340	0.333	0.745	0.746

Notes: See Table 10.

Appendix B

Table 13

Wald test results: long- and short-term symmetry.

	CAN		SWE		SWI		UK		US
H₀	1	2	3	1	2	3	1	2	3	1	2	3	1	2	3
Long-term symmetry
α₂ = α₅	0.613	0.538	0.080	2.749	1.656	1.855	2.659	0.014	15.653	0.200	0.047	0.055	0.001	0.014	1.440
α₂ = α₅	0.435	0.464	0.777	0.099	0.199	0.175	0.104	0.905	0.000	0.655	0.828	0.815	0.970	0.905	0.231
α₃ = α₄	0.437	1.755	8.726	1.961	1.801	1.348	0.981	1.640	4.754	0.071	0.531	0.266	0.589	5.880	1.873
α₃ = α₄	0.509	0.187	0.004	0.163	0.181	0.247	0.323	0.202	0.030	0.790	0.467	0.607	0.443	0.016	0.173
α₂ = α₃	0.854	1.625	6.780	0.193	0.014	0.648	0.530	2.323	7.355	0.128	0.148	1.192	0.175	2.876	7.885
α₂ = α₃	0.356	0.204	0.010	0.661	0.905	0.422	0.467	0.129	0.007	0.721	0.700	0.276	0.676	0.091	0.005
α₄ = α₅	0.904	0.611	2.962	2.141	4.431	4.387	0.467	1.379	0.011	0.000	0.542	0.000	2.732	5.375	1.080
α₄ = α₅	0.343	0.435	0.087	0.145	0.036	0.037	0.495	0.242	0.916	0.984	0.462	0.987	0.100	0.021	0.300
α₂ = α₃ = α₄ = α₅	0.885	0.712	2.918	1.445	2.719	2.724	1.584	2.185	6.837	0.127	0.217	0.544	2.584	4.137	2.938
α₂ = α₃ = α₄ = α₅	0.450	0.545	0.035	0.231	0.045	0.045	0.194	0.091	0.000	0.944	0.884	0.653	0.054	0.007	0.034
Short-term symmetry
	1.596	0.693	0.714	0.011	0.005	0.002	0.016	0.015	0.459	0.062	0.032	1.247	0.698	0.103	0.490
	0.208	0.406	0.399	0.916	0.944	0.969	0.899	0.904	0.499	0.803	0.858	0.265	0.404	0.748	0.485
	0.698	1.448	2.086	0.240	0.118	0.021	0.556	0.361	0.166	0.127	1.600	0.157	0.722	2.455	1.680
	0.404	0.230	0.150	0.625	0.731	0.886	0.457	0.549	0.685	0.722	0.207	0.692	0.396	0.119	0.196
	0.634	0.403	0.461	0.111	1.403	1.035	0.622	0.090	0.050	1.436	2.981	2.993	2.086	1.633	0.100
	0.427	0.526	0.498	0.739	0.237	0.310	0.431	0.765	0.824	0.232	0.086	0.085	0.150	0.203	0.752
	0.093	1.334	1.803	0.258	0.890	1.084	1.463	1.359	0.765	0.040	0.208	0.039	0.069	3.322	7.045
	0.761	0.249	0.181	0.611	0.346	0.299	0.228	0.245	0.383	0.841	0.649	0.843	0.793	0.070	0.009
	0.616	0.524	0.776	0.098	1.138	0.975	1.039	0.537	0.390	0.591	1.021	1.316	0.739	1.691	2.414
	0.605	0.666	0.508	0.961	0.334	0.405	0.376	0.658	0.761	0.622	0.384	0.270	0.530	0.170	0.067

Notes: 1. Probability reported under F-statistic value. 2. 1, 2 and 3 refer to respective regimes.

List of abbreviations and acronyms

AIC	Akaike information criterion
ARDL	Autoregressive distributed lag
BDSI	Association of the German confectionery industry (Bundesverband der Deutschen Süßwarenindustrie e.V)
BMI	Business monitor international
CAD	Canadian dollar
CAN	Canada
CHF	Swiss Franc
CN	Combined nomenclature
CPI	Consumer price index
ECM	Error-correction model
EUR	Euro
FFT	Food for Thought, S.A. (Switzerland)
FMOLS	Fully-modified ordinary least squares
FOB	First-on-board prices
GBP	British pound
German Sweets e.V.	German Association for the Promotion of Chocolate, Confectionery, Biscuit, Snack and Ice-cream Exports
IFS	Internatiobal Financial Statistics
IMB	International Markets Bureau (Canada)
LCPS	Local currency price stabilization
OECD	Organisation for Economic Co-operation and Development
OLS	Ordinary least squares
PPI	Producer price index
PTM	Pricing-to-market
SEK	Swedish krona
Std.Dev.	Standard deviation
SWE	Sweden
SWI	Switzerland
USD	American dollar

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1
Confectionery refers to chocolate, sugar confectionery and gum products (BMI 2010).
2
BMI (2010) reports the confectionery sector to be only fifth with 4.5% of total food and drink industry production, after meat and poultry processing (26%), dairy industry (13%), bread and baked goods (11%) and alcoholic beverages (7.8%).
3
Sugar confectionery includes hard boiled sweets, mints, jellies and medicated sweets (BMI 2010).
4
See Knetter (1989) for the details of the derivation.
5
The choice of thresholds is explained in Section 5.
6
Detailed outcome of this estimation can be obtained from the author by request.

Published Online: 2013-05-22

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Articles in the same Issue

https://doi.org/10.1515/jafio-2013-0003

Keywords for this article

pricing-to-market; asymmetric cointegration; nonlinear ARDL model; sugar confectionery