Natacha Broucqsault

Stéphane Roche

Julia Morere

Marie-Cécile Gaillard

Nicolas Levy

Karine Nguyen

Frédérique Magdinier

Modification of 4q35 and muscular gene expression in fetuses carrying a shortened D4Z4 array linked to FSHD

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

1 Centre de Re ´fe ´rence Neuromusculaire Nantes Angers, CHU Nantes, Nantes, France; 2 Centre de Re ´fe ´rence Neuromusculaire Nantes Angers, Atlantic Gene Therapy -Biotherapy Institute for Rare Diseases, Nantes, France; 3 Faculte ´de Me ´decine Nantes, Nantes, France FSHD is one of the most frequent forms of muscular dystrophy characterized by an early involvement of facial and scapular muscles with eventual spreading to pelvic and lower limb muscles. Few studies have been dedicated to sleep disorders in FHSD. Our objective was to explore subjective sleep quality in FSHD patients. Adults with genetically proven FSHD were included in the study. They were compared to a control group of subjects with no myopathy, no past neurological disease nor instable chronic disease history. The Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the clinical severity scale (CSS), the fatigue severity scale and the hospital anxiety and depression scale were used to evaluate the severity of the sleep disorder, the subjective sleep quality, the prevalence of daytime sleepiness, the anxiety and the depression in patients and controls. Pulmonary function and MRC score were also assessed. Mann Withney test, Spearman correlation and Fisher test were used for the statistics analysis. 22 FSHD and 36 controls were included in the study. Both groups were similar as for age, sexe, body mass index and respiratory support. 50% of FSHD patients presented with vital capacity <80%. The FSHD population had a significantly worse sleep quality (PSQI) than the control group (p < 0.01), with loss of subjective sleep quality, nocturne pain, bad dreams and day dysfunction due to sleepiness. Altered sleep quality was not correlated with the severity of the disease or with respiratory deficiency but was related with anxiety (p = 0.04). The latter was also correlated with depression, fatigue and bad dreams. Surprisingly, we noticed a negative correlation between ESS and CSS: the loss of activity in severe patients could result in harmony with sleep needs.

FSHD patients have altered subjective sleep quality as compared with control population. Anxiety mainly accounts for this, while severity of the disease and respiratory involvement do not affect it. http://dx.doi:10.1016/j.nmd.2013.06.642

P.16.6

Modification of 4q35 and muscular gene expression in fetuses carrying a shortened D4Z4 array linked to FSHD N. Broucqsault, S. Roche, J. Morere, M.C. Gaillard, N. Levy, K. Nguyen, F. Magdinier Inserm, UMR_S910, Marseille, France Facio-Scapulo-Humeral Dystrophy (FSHD) is an enigmatic pathology. This autosomal dominant disorder is linked to deletion within a D4Z4 macrosatellite in the subtelomeric 4q35 region. The gene product leading to the disease has not been clearly identified and epigenetic changes are likely key players in the disease since beside reduction in the number of repeats, D4Z4 is hypomethylated in FSHD. Within D4Z4, DUX4 has been found upregulated in patients. Different DUX4 transcripts have been described Production of a long transcript encompassing the DUX4 sequence and a region distal to D4Z4 encoding a toxic protein has been proposed as the cause of disease. A causal link between DUX4 expression and D4Z4 hypomethylation subsequent to array shortening has been proposed but never firmly established. We analyzed DUX4 expression as well as the expression of 4q35 genes and muscular markers in FSHD and non-FSHD biopsies during fetal development and in adults in a large cohort of samples. We highlight several genes whose expression differs between control and FSHD samples. Furthermore, we detected DUX4 transcripts in both groups, in muscle but also in other tissues indicating that expression of the long transcript is not restricted to FSHD muscles. Using FSHD and control myoblasts, we showed that DUX4 expression is induced by hypomethylation after knock-down of DNA methyltransferases, independently of D4Z4 array shortening. Our result tends toward a stochastic activation DUX4 transcription rather than a muscle-specific expression pattern in FSHD patients. The mechanism precluding onset and progression of FSHD remains highly controversial and still debated. Our work is the first to uncover changes in gene expression in fetuses carrying a D4Z4-linked 4q35 defect. These results are important for understanding FSHD but also in general, to understand how epigenetic mechanism modulate the transcription of repetitive DNA sequences in the human genome especially in the human diseases. The genetic locus of Facioscapulohumeral Muscular Dystrophy (FSHD) is only 25-50 kb from the telomere of Chr.4q, and shows an age-related onset of symptoms. This suggested that Telomere Position Effects (TPE) might regulate its poorly understood pathogenetic mechanism. FSHD patients show a reduction in the number of 3.3 kb D4Z4 repeats on at least one copy of chromosome 4. We first showed that continuous spreading of telomeric heterochromatin (classic TPE) could extend at least 100 kb into the subtelomeric region and increased Dux4-fl expression >10-fold when telomeres were short. We then examined whether telomere looping existed/influenced gene expression over much larger distances. We adapted the Hi-C technique to study the 4q region in an unbiased fashion. We established clonal myoblast cell lines containing a floxable hTERT that we removed at different times to initiate telomere shortening, producing isogenic subclones with different telomere lengths. We identified multiple novel long-range interactions at 4q associated with telomere shortening. We validated one interaction using 3C and 3D co-FISH experiments. A 4.8 Mb DNA loop present in FSHD myoblasts with long telomeres (20 Kb) and in cells obtained from unaffected age matched siblings (regardless of telomere length) was lost on the FSHD contracted allele when telomeres became shorter (9 Kb,long before telomeres became short enough to induce replicative senescence). Intriguingly, interactions involved several putative FSHD genes and a gene supposedly expressed only in cardiac muscle. Droplet-digital PCR (ddPCR) demonstrated changes in the abundance of different exon-pairs for a variety of candidate genes affecting FSHD in cells with short vs long telomeres, indicating telomere looping was at least altering splicing patterns if not overall transcription. These results suggest a role for telomere looping in FSHD pathology that could explain much of the age-related onset and variability in this disease. In healthy subjects, regular exercise is beneficial for mental and physical health, and post-exercise protein supplementation has been shown to enhance the physiological responses to training. FSHD is a muscular dystrophy characterized by slow progression and asymmetry of muscle weakness, often starting in facial, shoulder, humeral and calf muscles. Moderate, and even high-intensity exercise, has been shown to be well tolerated in these patients. In this double-blinded, placebo-controlled study,

  http://dx.doi:10.1016/j.nmd.2013.06.644 P.16.8 Does endurance training and protein supplementation improve fitness in patients with Facioscapulohumeral Muscle Dystrophy (FSHD)? G. Andersen, K.P. Prahm, J. Dahlquist, G. Citirak, J. Vissing Rigshospitalet, University of Copenhagen, Neuromuscular Research Unit, Department of Neurology, Copenhagen, Denmark

  Robin 1 , A.T. Ludlow 1 , G. Stadler 1 , F. Magdinier 2 , W.E. Wright 1 , J.W. Shay 1 1 UT Southwestern Medical Center, Cell Biology, United States; 2 Faculte de Medecine de La Timone, Marseille, France

	http://dx.doi:10.1016/j.nmd.2013.06.643
	P.16.7
	Length dependent telomere looping affects long-distant gene expression
	(5 Mb) in FSHD
	J.D.


Jean-Marc Solleder
email: jean-marc.solleder@unige.ch

Taxes

«INVESTISSEMENTS D'AVENIR» PORTANT LA RÉFÉRENCE «ANR-10-LABX-14-01

Keywords: Market power, export taxes, export policy, import demand elasticities JEL Classification: F13, F14

teaching and research institutions in France or abroad, or from public or private research centers.

Introduction

The most prominent theory of the determinants of trade policy postulates that when countries are setting their trade policies, they are likely to use their market power to manipulate their terms of trade. Insofar as all countries behave in a similar fashion, trade agreements are a means of avoiding a terms-of-trade-driven prisoners' dilemma [START_REF] Bagwell | A Theory of Managed Trade[END_REF][START_REF] Bagwell | An Economic Theory of GATT[END_REF][START_REF] Bagwell | The Economics of The World Trading System[END_REF]. The question of the relationship between market power and trade policy, while central to the theory, is in essence an empirical matter. Several major contributions to the literature link market power to the determination of import tariffs [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF][START_REF] Bagwell | What do trade negotiators negotiate about? Empirical evidence from the world trade organization[END_REF][START_REF] Ludema | Do terms-of-trade effects matter for trade agreements? Theory and evidence from wto countries[END_REF][START_REF] Nicita | Cooperation in WTO s Tariff Waters?[END_REF], thus providing strong support for the terms-of-trade rationale as the key determinant of trade policy. Tariffs, however, are only one element of trade policy. Export policies are rarely the focus of empirical studies. A major reason for this is that they are less covered by the WTO disciplines. Nor are export taxes are systematically documented. To date, the question of the importance of market power as a determinant of export taxes remains unexplored. This paper fills that gap. Following the approach developed for imports in [START_REF] Nicita | Cooperation in WTO s Tariff Waters?[END_REF], I use a framework in which the absolute value of the inverse of rest-of-the-world import demand elasticity faced by exporters is a proxy for their market power in a sample of 39 countries at the 6-digit level of the Harmonized Standard (HS). My results highlight a positive effect of market power on export taxes, providing support for the terms-of-trade rationale.

These results are important for at least two reasons. The first reason is that, for most members, export taxes fall outside of the WTO disciplines. 1 They are thus a testbed of choice to analyze to what extent countries are using market power to their advantage when setting trade policies. Second, because governments are increasingly resorting to export taxes [START_REF] Fliess | Taking stock of measures restricting the export of raw materials: Analysis of OECD inventory data[END_REF], the importance of market power as a determinant of such taxes is a question of great policy relevance. It is therefore important to better understand the determinants of such policies.

There are three challenges to overcome in order to estimate the impact of market power on export taxes. The first is to estimate the import demand elasticities faced by each exporter. To do this, I adapt the methodology developed by [START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF] for import demand elasticities by defining market power as the inverse of the absolute value of these elasticities. I then estimate the relationship between market power and the rate of export taxes. A second challenge is that data on export taxes is scarce. To circumvent this, I extend Solleder's (2013a) dataset from 20 to 39 countries and use this new dataset for my analysis. A third challenge is that the results may face an endogeneity issue. I tackle this using an IV regression approach. This paper contributes to the empirical literature on trade policy as well as on export taxes. It advances the first strand of research by examining the terms-of-trade rationale as a determinant of trade policy. While theoretical contributions linking market power and import taxes are abundant (see, e.g., [START_REF] Bagwell | A Theory of Managed Trade[END_REF][START_REF] Bagwell | An Economic Theory of GATT[END_REF][START_REF] Bagwell | The Economics of The World Trading System[END_REF], [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF] were the first to show empirically that the effect of market power on 1 With the exception of recently acceded countries.

tariffs is economically significant by regressing their proxy for market power2 on import tariffs. Their analysis is limited to tariff-setting outside the WTO system. Countries in their sample may therefore share some common characteristics that might, in turn, influence the results. In contrast, 37 countries out of 39 in the sample of this paper are WTO members. [START_REF] Bagwell | What do trade negotiators negotiate about? Empirical evidence from the world trade organization[END_REF] identify terms-of-trade considerations in the accession commitment to the WTO by analyzing the magnitude of the tariff reduction following a country's accession to the WTO. This magnitude should be higher to the extent that the country's ability to influence world prices is greater, its import share is larger, and the rate at which domestic distortions rise with tariffs is smaller. Using these metrics, they find support for the terms-of-trade hypothesis. [START_REF] Ludema | Do terms-of-trade effects matter for trade agreements? Theory and evidence from wto countries[END_REF] develop a model allowing them to find evidence of the terms-of-trade rationale in an MFN setting within the WTO, thus generalizing to WTO members the findings of [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF]. In a more recent contribution, [START_REF] Nicita | Cooperation in WTO s Tariff Waters?[END_REF] extend Broda et al.'s (2008) analysis to tariff negotiations within the WTO framework. They show that tariffs are positively correlated with market power when they are set in a non-cooperative fashion (in the presence of tariff water) and negatively correlated with market power when tariffs are set cooperatively (in absence of tariff water). The aforementioned papers concentrate either on the behavior of policy makers directly within the WTO framework or on policies which are normally subject to WTO discipline. My paper differs from these contributions in that it studies how countries set export taxes, rather than import taxes. This is an important distinction as export taxes are not regulated under the WTO and are, therefore, more likely to be set freely by policy makers. This paper also extends the current literature on export taxes. Empirical contributions on export taxes are mainly concerned with their trade impact (see, e.g., [START_REF] Estrades | The Role of Export Restrictions in Agricultural Trade[END_REF][START_REF] Laborde | A Global Assessment of the Economic Effects of Export Taxes[END_REF]Solleder, 2013b) or are centered on a single product or industry (see, e.g., [START_REF] Bouët | Food crisis and export taxation: The cost of noncooperative trade policies[END_REF][START_REF] Bouët | Differential export taxes along the oilseeds value chain: A partial equilibrium analysis[END_REF][START_REF] Deese | Export Taxes on Agricultural Products: Recent History and Economic Modeling of Soybean Export Taxes in Argentina[END_REF][START_REF] Flaaten | Triple win for trade in renewable resource goods by use of export taxes[END_REF]. Looking at the determinants of export taxes, Piermartini (2004) identifies the major arguments about how they are set. She discusses the validity of the following types of arguments in favor of export taxes: terms of trade, stabilization of domestic prices, control of inflationary pressure, protection of infant industries, tariff retaliation, government revenue collection, and income redistribution. She highlights the fact that while a country with market power may improve its terms of trade by setting an export tax, this terms-of-trade argument relies on assumptions that may be hard to meet.3 Similar concerns over the terms-of-trade rationale for the setting of import tariffs are underlined by [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF]. Closer to this paper, [START_REF] Estrades | The Role of Export Restrictions in Agricultural Trade[END_REF] investigate the effect of export taxes on the prices of agricultural products when a country has market power. They consider that a country has market power when it exports more than 15% of the world trade for the concerned product at the 6-digit level of the Harmonized System. They reduce the sample to countries exhibiting market power in each sector, estimate their gravity model with the restricted sample and compare their results with those of the full sample. They do not find evidence of stronger price effects for countries with market power. Nevertheless, their proxy for market power differs from the theoretically grounded inverse of import demand elasticity as defined in this paper. Their analysis is also limited to a very specific type of goods, (agricultural products), while this paper investigates all products.

The rest of the paper is organized as follows: Section 2 introduces the theoretical background and empirical methodology related to the main question. Section 3 presents the data. Section 4 describes the method and data used to compute the rest-of-the world import demand elasticities. Section 5 discusses the findings, and Section 6 concludes.

Methodology

The idea that optimal export taxes are linked to trade elasticities dates back to [START_REF] Bickerdike | The Theory of Incipient Taxes[END_REF]. Under perfect competition in a two-country case, it can be shown4 that:

1 1
where T is the ad-valorem tax and is the trade elasticity faced by the country of reference. When the country of reference imports the good, the relevant trade elasticity is the export supply elasticity of the rest of the world. When the country of reference is an exporter, it is the import demand elasticity of the rest of the world that matters. [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF] show that this result extends to more general settings and holds even if the objective of the government is not to maximize social welfare. 5Thus an increase in market power, measured by an increase in the inverse of the absolute value of the import demand elasticity of the rest of the world, will imply a higher optimal export tax rate. This suggests a positive relationship between market power and export tax rate.

To estimate Equation (1), I use the following specification:

1 2
where c indexes countries, n products at the 6-digit level of HS classification. is the rate of the export tax on product n in country c and is the absolute value of the inverse of the import demand elasticity from the exporter's point of view (see Section 4) and is my proxy for market power. γ c , and γ HS2 are, respectively, country, and sector fixed effects, included to control for unobserved heterogeneity.

is a fixed effect controlling for the year the data on export taxes was collected, and is the error term.

Note that my measure of market power is time invariant. This is due to the way the rest-of-the-world import demand elasticities are estimated (see Section 4). Consequently, I do not use time variation in export taxes. 6 Whenever more than one period was available for export taxes, the most recent time period was chosen for estimations. The year for which export taxes were collected changes by country, so I include the collection year dummy to control for any time-related change in the magnitude of the export taxes. It may be, for example, that taxes imposed during the 2007-2008 food crisis have a higher magnitude than those that had been imposed previously.

I expect a positive and statistically significant estimate of α, meaning that taxes are set at a higher value when an exporter has market power, as predicted by theory. 7 In addition to the paucity of data, I face several potential issues in my estimation. First, taxes imposed by China constitute an important share of the export tax dataset I am using. This may be a problem since, unlike most other countries, China had to make concessions on its use of export taxes during its accession to the WTO. 8 To ensure that the results are not driven by a behavior specific to China, I reestimate my model after excluding China from the sample. Second, some entries in the dataset exhibit characteristics that may lead to a bias in the estimation. 9 I again reestimate the model, controlling for those taxes with dummies.

Data

Estimating market power effects on export taxes would ideally require a comprehensive and exhaustive dataset on such taxes. In stark contrast with import taxes, to date, there is no such dataset. To the best of my knowledge, there are currently four publicly available multi-country datasets covering export taxes. Two of them, maintained by the OECD, concentrate on industrial raw materials and on primary agriculture products, respectively. 10 Estrades et al. (2017) have collected a dataset of export restrictions on agricultural products. 11 Finally, Solleder (2013a) collected export taxes without limitation on the type of products for 20 countries for her Panel Export Taxes (PET) dataset. 12 The first three columns of Table 1 show a summary of the content and coverage of those datasets.

This paper uses an extended version of the PET dataset reported in column 4 of Table 1. The original PET dataset kept only countries for which time variation in the setting of export taxes was available. This restriction is lifted for the dataset used in this paper. The coverage is therefore extended to 39 countries, 6 My dataset nonetheless contains export taxes for two time periods for about half of the countries.

7 Equation (1) suggests a value of exactly 1 for the coefficient α. For this to happen, several conditions should be met: first, elasticities should be estimated precisely; second, legislators should have exact knowledge of the market power of their country for each product; and, finally, there should be no other reason for imposing export taxes.

8 Export taxes are limited to the goods defined in Annex 6 of China's WTO accession protocol and are bound. The average non-zero bound export tax rate is 28%, about 8 percentage points higher than the average tax rate in my dataset.

9 Some taxes have been applied at a higher level of disaggregation than the internationally comparable 6-digit HS and others are expressed in specific forms that required conversion. 10 Both of these are available on the OECD website.

11 This dataset is available from the authors.

making this dataset the largest available in terms of country coverage. The data manual for the OECD dataset (OECD, 2016) states that the organization should survey, in priority, countries with a high market share in the goods on which they are focusing. As my variable of interest, market power, is likely to be correlated with market share, there is a high risk of sample selection bias with those datasets. In contrast, the data collection of the PET and its extended version is orthogonal to my research question. Additionally, the PET dataset and the extended version are the only datasets not restricting the coverage to a set of products. About 6% of the tax registered in the extended PET dataset cannot be attributed to raw materials or agricultural products as defined by OECD (2016).

The 39 countries in the extended PET dataset are presented in The extended PET dataset is a positive list, meaning that only non-zero taxes are included. I complete this list with non-taxed products. Instead of adding a zero for each product at the HS6 level, I select only those products that each country has exported at least once over a 10-year period. The rationale for this is that, unlike for imports, countries are not able to export the whole set of goods and are less likely to regulate the exports of products they have never exported. The percentage of taxed products among the products actually exported by the country is shown in parentheses in the third column of Table 2. Cambodia is the country that applies taxes on the highest share of products it exports, with more than 9% of its exported products being covered. The Solomon Islands come next as the 74 products it taxes represent 5.4% of the total products it exports. China follows with 4.9%; all of the other countries apply taxes to less than 4% of the products they export. The average tax rate in the dataset drops to 0.23% when considering zero taxes.

As the elasticities used as a proxy for market power are not time varying (see Section 4), I do not need the time variation and retain only the most recent time period. The last column of the table indicates for which year the information in the dataset was collected. With few exceptions, data are collected within a window covering 2007-2011. where the subscripts n and k index goods, the subscripts m and l index endowments and superscript t indicates a time-varying variable. is the unit price of good n at time t.

is the value of endowment m at time t.

To ensure that Equation (3) is consistent with the assumptions used to obtain Equation (1), I assume perfect competition, implying that each good n is homogeneous (∑ 1) and that the price of good n is exogenous. Furthermore, I impose constant return to scale (∑ 1) and ensure that Young's theorem is not violated by imposing ank = akn and bnk = bkn.

As I am interested in the import demand elasticity faced by each exporting country, I need to aggregate Equation (3) over all countries except the exporter of interest. I then take the derivative of this aggregated translog with respect to and obtain:

, ≡ , , , 1
1 ln 1 ln ln 4
where , ) is the share of goods in the world's GDP that is exported by the considered country. As this share is an input to the aggregated translog function, it is negative.

Estimating directly from Equation ( 4) is not technically possible because the number of covariates would be too high. To circumvent this problem, I follow [START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF] and aggregate all non-n goods in the aggregated economy using a Tornqvist price index net of the price of good n. 13 Doing this requires the parameters of the translog function to be time invariant. Next, in order to have enough time variation to estimate a nn by country accurately, I pool the data and estimate a common a nn using both cross-country and time variation. I introduce year-product and country-product fixed effects to control for country and year specific shocks on the share of good n in the rest of the world's GDP. The estimated equation is then:14 1 ln ; ln 5

The import demand elasticity for good n in the rest of the world can be expressed as:

1 1 6
where is the average share for country c over all time periods.

Equation ( 6) is still subject to econometric issues. The estimates of may not be consistent, mainly for the following three reasons: first, there are endogeneity and measurement errors in the unit price; second, we only observe price when trade happens, which lead to a selection bias; third, exports may not adjust immediately after a change in price. To address these issues, I implement the corrections suggested by [START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF]. I use instruments for unit prices and the price of all other goods and estimate the model using a selection model in panel data with unobserved country effects following Semykina and Wooldridge (2010). I also check for serial correlation in the data and, when needed, estimate the model with a system GMM estimator as advised by Roodman (2009).

Data used in the estimation of elasticities

Value and quantity data on trade flows were sourced from the UN Comtrade Database (UNSD, 2017). I use mirrored information on import trade flows instead of data on exports, as the former is more reliable. Unit prices are computed by dividing the value of the trade flow by the quantities converted in kilograms. When conversion to kilograms was impossible or quantity data was unavailable, the applicable observation has been dropped. To reduce the noise in the resulting unit prices, I exclude goods for which the traded value is inferior to 2,500 USD each year during the period under consideration. 15 Data on capital stock is not readily available. I estimate it using the Gross Fixed Capital Formation indicator of the World Development Indicators (World Bank, 2016). Following Berlemann and Wesselhöft (2014), I regress the year on the log of the gross capital formation for each country and then compute , where is the capital stock in the previous period, I t the gross fixed capital formation, g i the coefficient of 13 Caves et al. (1982) show that the Tornqvist index for a translog with time-invariant parameters is the GDP deflator. Thus the adjusted Tornqvist price index is: ln ln / 1 where and the GDP deflator.

the log of gross capital formation from the aforementioned regression and σ the depreciation rate of capital, set to be 4% because it is the average depreciation rate in the Penn World Tables [START_REF] Feenstra | The next generation of the penn world table[END_REF].

Data on agricultural land, labor force and GDP are sourced from the World Development Indicators (World Bank, 2016). The GDP deflator is computed based on the GDP series in constant and current USD.

Estimated elasticities

I estimate 491,195 import demand elasticities faced by exporters, among which 40,338 (about 8% of the sample) are positive. These aberrant elasticities are eliminated from the sample. 16 Next, I deal with extreme outliers by eliminating the 1% tails on each side of the remaining elasticities' distribution.

My final set consists, therefore, of 441,839 elasticities, for which summary statistics are given in Table 3. The magnitude of the elasticities range from -20.78 to -0.25, with optimal export taxes therefore ranging from 4% to 400%. The mean elasticity is -1.29 suggesting a relatively high average optimal export tax of about 77%. I compute standard errors for each elasticity.17 About 89% of the elasticities contained in the final set are statistically significantly different from zero with a 95% confidence level.

The table in Appendix D shows the average import demand elasticity faced by each country in the dataset. The countries with the lowest average elasticity in absolute value and therefore the highest market power are the United States, Germany, Italy, France, and the United Kingdom. At the other end of the distribution, the countries facing the highest import demand elasticities are Palau, Wallis and Futuna, Montserrat, Kiribati, and Guinea-Bissau.

External tests for the estimated elasticities

I provide three external tests for the estimated elasticities. First, drawing on the identity linking aggregate imports and exports, it can be shown (see Appendix B) that the import demand elasticity faced by the exporter is equal to a weighted sum of import demand elasticities calculated from the importer's point of view and the export-weighted sum of the export supply elasticities from the point of view of the exporter:

, 1 → → 7
where , is the import demand elasticity from the point of view of the exporter for country I, the import demand of the entire world, the export supply elasticities from the point of view of the exporter, → / the share of exporter c in the world exports of a given product and, 1/ → / the inverse share of i in world's exports. Using Equation ( 7) with data from [START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF] for and [START_REF] Nicita | Cooperation in WTO s Tariff Waters?[END_REF] for , I can construct a proxy to validate the import demand elasticities I estimated. I then regress my elasticity estimates on this proxy. Second, I follow [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF] and regress my estimates on the GDP of the exporting country and its remoteness, defined by the inverse distance weighted GDP of all other countries in the world. Finally, I regress my estimates on a dummy indicating whether the goods are homogeneous according to the classification made by Rauch (1999). Homogeneous goods should exhibit a higher elasticity.

The results of these tests are presented in Table 4. Column (1) shows the result of the regression of the log of the absolute value of the proxy for the import demand elasticities as defined by Equation ( 7) on the absolute value of my elasticities. As expected, the relationship is positive and statistically significant with a 99.9% confidence level.18 Column (2) shows a negative relationship between the absolute value of the elasticities and both GDP and remoteness. The first result suggests that having a larger GDP decreases the magnitude of the elasticities faced by the country and, hence, increases its market power. The second one indicates that countries located far from world markets are more likely to have market power. According to [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF] and [START_REF] Nicita | Cooperation in WTO s Tariff Waters?[END_REF] this stems from their capacity to absorb more of the regional demand as they have smaller trade costs than the rest of the world. Column (3) presents the result for the estimation where I regress the absolute value of my elasticity estimate on a dummy indicating whether the good is homogeneous as defined by Rauch (1999). As expected, the coefficient of this dummy is positive and statistically significant, meaning that homogeneous goods exporters face an elasticity of a higher magnitude than non-homogeneous goods exporters, and hence have lower market power. In sum, all tests give statistically significant results with expected sign for the coefficients. Robust standard errors in parentheses * p < 0.05, * * p < 0.01, * * * p < 0.001 5. Does market power influence export taxes?

Baseline results

The baseline regression results19 of the model presented in equations ( 1) and ( 2) are given in Table 5. The first four columns introduce the results of OLS regressions of market power (columns (1) and ( 3)) or its log (columns (2) and ( 4)) on export taxes. The models in columns (1) and (2) do not include fixed effects, while columns (3) and (4) add country, year, and sectoral level (HS2) fixed effects, as presented in Equation (2). The coefficient on market power is positive and significant without fixed effects, but loses its significance when the fixed effects are introduced. The log of the market power is significant and positive for all OLS regressions. The loss of significance of the market power coefficient was expected as market power is measured noisily. Taking its log reduces this issue. The magnitude of the OLS coefficients is not straightforward to interpret. By standardizing it, I find that an increase of one standard deviation in the log of market power triggers an increase of about 0.028 percentage points in the tax rate in the model with fixed effects (column (4)). While this value might seem small, recall that most exported products are not taxed. Hence, the average tax rate including non-taxed products in my sample is 0.23. This implies that at the sample mean, a one-standard-deviation increase in market power leads to about a 10% increase in the rate of export tax.

To get a clearer view of the magnitude of the effect of a change of market power and considering that taxes cannot be negative, I estimate the same model using a Tobit left censored at zero. Columns ( 5) and ( 6) show the results of the Tobit regression. All coefficients are statistically significant and positive. The standardized effect now shows an increase of 2.29 percentage points in the tax rate when the log of market power increases by one standard deviation, which is more in line with what is observable in the tax rate of the products subject to tax. This standardized effect is about 13% of the average tax rate of the products subject to a tax.

Controlling for endogeneity

The estimates presented in Table 5 may be subject to an endogeneity issue as export taxes are likely to affect unit prices used to compute the elasticities. To control for this, I use an instrumental variable approach.

Following [START_REF] Broda | Optimal tariffs and market power: The evidence[END_REF], I use the average market power of the neighboring countries for the relevant good as an instrument for the market power of the country of interest. I reestimate Equation (2) using IV and IV Tobit estimators.

Results for these regressions are presented in Table 6. Columns (1) and ( 2) simply show the results of a standard OLS to ensure that the subsample used in the IV regressions yields results that are similar to those of the full sample used in Table 5 above. The results are similar to the third decimal for the significant coefficients. Columns ( 3) and (4) present the results for an IV regression and columns ( 5) and ( 6) for an IV Tobit regression. The Kleibergen-Paap (K-P) statistics are presented for both IV regressions. Their values are well above the rule of thumb threshold value of ten and the thresholds given by Stock and Yogo (2005), suggesting that the instruments are not weak. All coefficients of both IV and IV Tobit regressions remain positive and significant. The magnitude of the coefficients remain in the same range as those in Table 5, with the exception of market power in the IV Tobit regression, which is about six times higher than its noninstrumented counterpart.

Robustness checks

To ensure that the results presented above are not driven by outliers or external factors, I carry out two robustness checks.

First, my export taxes dataset contains information on taxes applied at the National Tariff Line level. Since my analysis is performed at the HS6 level, the magnitude of the taxes might be incorrectly interpreted after aggregation. In addition, several export tax rates in my dataset are specific, that is, expressed as a value per physical unit. Solleder (2013a) computed ad valorem equivalents for such taxes to include them in the dataset, but their behavior and the reason for which they have been applied may differ from the other taxes in the sample. To control for this, I remove them from the dataset and reestimate the models presented above.

Second, during its accession to the WTO, China had to make concessions on export taxes. This means that China may not behave in the same way as other countries that can set their export taxes at will. To ensure that the results are not influenced by China, I rerun my baseline regression with China removed from the sample.

Table C1 and C2 in Appendix C introduce the results of the Tobit regressions with and without instruments, respectively. In both tables, the first two columns introduce the results for the sample without partial or specific taxes, as defined above, and columns ( 3) and ( 4) present the results of regressions without China. All coefficients remain positive and significant with the exception of the coefficient on market power in the first column of the Tobit regressions, which loses significance. The coefficients remain in the same order of magnitude as the base regressions presented above.

Conclusion

This paper investigates the extent to which countries consider their market power when setting export taxes. Greater market power, as measured by the absolute value of the inverse import demand elasticity faced by an exporter, implies a higher optimal export tax rate. I test this prediction using new estimates of market power at the 6-digit level of the Harmonized System. My results confirm the theoretical prediction and demonstrate that countries set a higher export tax rate for goods for which they have higher market power. These results are robust to the exclusion of China which, unlike most other countries, is bound by its WTO commitments on export taxes.

These results are important because they lend support to one prediction of the terms-of-trade theory (Bagwell andStaiger, 1999, 2002) on the formation of trade agreements: that countries, when not constrained by international regulation, tend to use their market power when setting their trade policy. Since export taxes are not covered by WTO disciplines, they are thus a testbed of choice. At the policy level, these results suggest that there is room for greater regulation of export taxes at the multilateral level and in the framework of preferential trade agreements. where E * is ROW's expenditure function, U * its utility, R * its revenue function, and * its factor endowments. ROW net import demand vector is given by: where M * is the vector of net import to ROW and the index P indicates the first derivative with respect to P * . As we are in a two-country setting, it must be that the net import to Home is equal to the opposite of the net import to ROW: M = -M * . Using a Meade utility function,20 home utility is given by U = φ(M) with P, the Home price vector, being proportional to φ M (M). Taxes are thus implicitly defined as the wedge between Home and ROW prices: t = P -P * . Note that as M is the net import vector, for any single good j, having M j < 0 means that Home is exporting this good to ROW. Moreover, for any exported product j, a negative t j will indicate an export tax.

A change in the offered price vector dP * will lead to a change in the net import to Home of -dM * = -M P * (P * )dP * . The change in home utility can therefore be expressed as: * * * * *

. * 10 where α is a scalar reflecting price normalization in Home. Substituting with the result found above for -dM * , we get:

. * * * 11 Thus, . * * is the gradient vector of U when expressed as a function of P * . For an optimum choice of P * , this gradient vector must be zero: * * 0 12

where the exponent T indicates a transpose.

Knowing that t = P -P * , we have: * * * 0 13 * * * * * 0 14

Differentiating with respect to P * , the trade balance condition P * M * (P * ) = 0 yields (P * ) T M P * (P * ) + (M * ) T = 0, replacing the first term in Equation ( 14), which yields: * * * 15 which defines t in terms of the price elasticities of the trade offer from the ROW.

Switching to a two-goods case, Equation ( 15) can be rewritten as:

Equation ( 24) is used to construct the import demand elasticities from the point of view of the exporter, which are used in the external check of the main elasticities.



  OECD (2016). Methodological Note to the Inventory of Restrictions on Exports of Raw Materials. pages 1-41.  Piermartini, R. (2004). The role of export taxes in the field of primary commodities. WTO Discussion Papers 4, World Trade Organization (WTO), Economic Research and Statistics Division.  Rauch, J. E. (1999). Networks versus markets in international trade. Journal of International Economics, 48(1):7-35.  Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in Stata. Stata Journal, 9(1):86-136.  Semykina, A. and Wooldridge, J. M. (2010). Estimating Panel Data Models in the Presence of Endogeneity and Selection: Theory and Application. Journal of Econometrics, 157(2):1-56.  Solleder, O. (2013a). Panel Export Taxes (PET) Dataset: New Data on Export Tax Rates.  Solleder, O. (2013b). Trade Effects of Export Taxes.  Stock, J. H. and Yogo, M. (2005). Testing for Weak Instruments in Linear IV Regression. Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg, 2001(February):80-108.  UNSD (2017). UN Comtrade -International Trade Statistics Database.  World Bank (2016). World Development Indicators 2016.

Table 2 .

 2 The data displays large heterogeneity along all dimensions covered. The first two columns show the average tax rate and standard deviation, considering taxed products only, in each country. Countries impose very different tax schedules with average tax rates ranging from 0.67% (Norway) to 96.52% (Brazil) with a global average of 18.34%, excluding products not subject to taxes. Several countries are imposing a uniform tax rate on the products they choose to tax. Pakistan, for example, taxes 97 6-digit HS products at the flat rate of 25%. Note that this is not necessarily in contradiction with my hypothesis that market power influence tax rate as long as market power influences the selection of the taxed products. In contrast, Nepal exhibits the highest standard deviation of the set with taxes ranging from less than 1% to 200%. The extent to which countries resort to export taxation is also heterogeneous. The third column of Table2indicates the number of products, defined at the 6-digit level of the Harmonized Standard (HS). Cambodia and China come first, with 297 and 242 6digit HS products taxed, respectively. All others apply taxes on fewer than 200 HS codes, with Canada and Zimbabwe taxing a single HS product each.

Table 1 :

 1 Datasets on Export Taxes, adapted from Solleder (2013a)

		PET	OECD	ERA	Extended PET dataset
		(Solleder, 2013a)	(Fliess and Mard, 2012) (Estrades et al., 2017)	This paper
	Countries applying	20 countries	23 countries (raw	25 countries	39 countries
	export taxes		materials); 9 countries
			(agricultural goods)
	Years	2 years	Several	Several	Cross section, but data
		(2000-2011)	(2002-2012)	(2005-2014)	collected over different
					years
	Commodities	All goods	Agricultural goods,	Agricultural goods	All goods
			Raw materials
	Disaggregation	HS6 and NTL *	HS6 and NTL *	HS6	HS6
	HS Revision	HS-2002	HS-2007	HS-2002	HS-1992
	Type of export	Export Taxes	Export Taxes + other	Export Taxes + other	Export Taxes
	restrictions		export	export
			restrictions	restrictions
	Value	Export Tax Rate and	As reported by the	Ad valorem tax rates,	Export Tax Rate and ad
		ad valorem	official source	specific tax rates,	valorem equivalent for
		equivalent for		dummies for other	specific taxes
		specific taxes		restrictions
	Temporary taxes	Included	Included	Included	Included
	* National Tariff Lines

Table 2 :

 2 Summary statistics for countries in the extended dataset . Estimating import demand elasticities from the exporter's point of view 4.1. Methodology Following the methodology developed for import demand elasticities by[START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF], based on the work of[START_REF] Kohli | Technology, Duality, and Foreign Trade: The GNP Function Approach to Modeling Imports and Exports[END_REF], I use a revenue function approach to estimate import demand elasticities faced by exporters at the 6-digit level of the Harmonized System. I assume that each country can be modeled as a GDP / revenue function, which is common across all countries up to a constant term. This GDP function, denoted , is a function of prices and endowments as in[START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF] and[START_REF] Nicita | Cooperation in WTO s Tariff Waters?[END_REF]. I assume this GDP function R to have a flexible translog functional form:

	Country name	Average	Standard	Number (percentage)	Year
		tax rate, % deviation	of taxed products	collected
	Antigua and Barbuda	14.8	13.26	33 (1.0%)
	Argentina	28.1	18.37	26 (0.5%)
	Azerbaijan	2	0.73	6 (0.2%)
	Bangladesh	10	0	2 (0.1%)
	Belarus	23.7	14.16	12 (0.3%)
	Belize	8	0	5 (0.2%)
	Brazil	96.5	69.63	29 (0.6%)
	Cambodia	15.6	13.55	297 (9.8%)
	Canada	15	NA	1 (0.0%)
	China	20.3	18.83	242 (4.9%)
	Cote d'Ivoire	18.9	3.62	10 (0.3%)
	Dem. Rep. of Congo	1.2	0.44	63 (1.8%)
	Egypt	26.5	22.30	30 (0.6%)
	Ethiopia	92.5	71.21	12 (0.4%)
	Fiji	3	0	11 (0.3%)
	Gambia	5	0	3 (0.2%)
	Guatemala	1	0	5 (0.1%)
	Iceland	5	0	65 (1.7%)
	Indonesia	16.6	9.90	16 (0.3%)
	Kenya	20	0	25 (0.5%)
	Malawi	50	0	12 (0.5%)
	Malaysia	10.7	29.27	60 (1.2%)
	Mongolia	3.5	2.33	2 (0.1%)
	Nepal	89.1	129.56	60 (1.9%)
	Norway	0.7	0.24	108 (2.3%)
	Pakistan	25	0	97 (2.1%)
	Papua New Guinea	5	0	41 (1.8%)
	Philippines	20	0	48 (1.0%)
	Russia	12.2	12.65	145 (3.0%)
	Solomon Islands	12.9	9.58	74 (5.4%)
	South Africa	5	0	5 (0.1%)
	Sri Lanka	32.8	28.60	37 (0.9%)
	Thailand	5	0	57 (1.2%)
	Tunisia	2.5	2.91	95 (2.2%)
	Uganda	15.7	8.09	26 (0.6%)
	Ukraine	26.1	8.24	52 (1.1%)
	Vietnam	14.4	10.74	143 (3.0%)
	Zambia	22.7	4.39	13 (0.4%)
	Zimbabwe	20	NA	1 (0.0%)
	Complete dataset:	18.34	31.38	1,969 (1.3%)	-

Source: Author's calculations.

Notes: products are defined by 6-digit HS codes; when more than one time period was available, only the most recent was considered; average tax rate and standard deviations do not consider non-taxed products. 4

Table 3 :

 3 Summary Statistics for Import Demand Elasticities Faced by Exporters

		Mean	Median	Standard Deviation	Minimum	Maximum	Number
	Elasticities	-1.29	-1.00	1.49	-20.78	-.25	441,839

Table 4 :

 4 Regression results for the external tests of elasticity estimates

		(1)	(2)	(3)
		log(Absolute value of el. estimates)
	log(proxy)	0.00361***
		(0.000304)
	log(GDP)		-0.00329***
			(0.000256)
	log(remoteness)		-0.00447***
			(0.000571)
	Homogeneous good dummy			0.0263***
				(0.00352)
	R 2	0.250	0.240	0.100
	Country fixed effects	Yes	No	Yes
	HS6 fixed effects	Yes	Yes	No
	Obs.	77,137	76,211	88,835

Table 5 :

 5 Baseline regressions for market power on tax rate

		OLS		OLS			Tobit
		(1)	(2)	(3)	(4)	(5)	(6)
		Tax rate	Tax rate	Tax rate	Tax rate	Tax rate	Tax rate
	Market power	0.0937 * * *		0.0515		3.165 * * *
		(0.0329)		(0.0324)		(0.250)
	log(Market P.)		0.0696 * * *	0.0725 * * *		5.739 * * *
			(0.0183)		(0.0215)		(0.202)
	Year FE	No	No	Yes	Yes	Yes	Yes
	Country FE	No	No	Yes	Yes	Yes	Yes
	H2 FE	No	No	Yes	Yes	Yes	Yes
	Obs.	101,993	101,993	101,993	101,993	101,993	101,993
	Robust standard errors in parentheses
	* p < 0.1, * * p < 0.05, * * * p < 0.01

Table 6 :

 6 IV Regression results:

		OLS on IV sample	IV			IV Tobit
		(1)	(2)	(3)	(4)	(5)	(6)
		Tax rate	Tax rate	Tax rate	Tax rate	Tax rate	Tax rate
	Market Power	0.0165		0.231 * *		19.63 * *
		(0.0268)		(0.0989)		(9.202)
	log(Market P.)		0.0778 * * *		0.113 * *		9.146 * * *
			(0.0228)		(0.0483)		(3.476)
	Year FE	Yes	Yes	Yes	Yes	Yes	Yes
	Country FE	Yes	Yes	Yes	Yes	Yes	Yes
	H2 FE	Yes	Yes	Yes	Yes	Yes	Yes
	K-P F-stat	-	-	31123.41	235756.42	-	-
	Obs.	84391	84391	84391	84391	84391	84391
	Robust standard errors in parentheses
	* p < 0.1, * * p < 0.05, * * * p < 0.01

They define market power as the inverse of the export supply elasticity faced by the importers, estimated at 4-digits of HS using a methodology developed by[START_REF] Broda | Globalization and the Gains From Variety[END_REF].

Setting the export tax must not trigger retaliation from trade partners. The tax must not trigger the development of substitutes for the taxed good. The exact import demand elasticity of the rest of the world, as well as the degree of contestability of the market, must be known in order to set up an optimal tax.

See Appendix A for a demonstration based on[START_REF] Dixit | Theory of International Trade: A Dual, General Equilibrium Approach[END_REF].

They show, for example, that the optimal tax in a[START_REF] Grossman | Protection for Sale[END_REF] setting, when the government is subject to lobbying, is equal to the inverse elasticity, as in Equation (1) plus a second term reflecting the importance of lobbying.

Note that the logs of the factor endowments have been normalized in order to ensure regularity conditions on .

[START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF] also eliminate elasticities with an unexpected sign (5% of their sample). After performing these operations, the standard deviation of the elasticity in my set is equal to 1,257, with the lowest elasticity being -297,416.

The standard error of the elasticity is given by the standard error of the coefficient of 1 , divided by the share .

The actual correlation coefficient between my elasticities and the proxy is 0.23, which is reasonable given the facts that those elasticities are estimated noisily and all three elasticity sets were estimated for different time periods.

Note that while the elasticities are estimated for a wide range of countries, only countries for which data on export taxes is available are considered in these regressions.

Of the form φ(M,V ) = maxx{f(X + M)|X,feasible}, where X is the local production made using local inputs V, and M is a gift vector of goods. This allows us to concentrate on trade and leave production aside.

16

≡ * 1

The author gratefully acknowledges support from the French National Research Agency under program ANR-10-LABX-14-01.

Appendix A: Development of the link between export taxes and elasticities Suppose a two-country setting: Home and the rest of the world (hereafter ROW), denoted by * under perfect competition. Home is able to influence world prices and offers goods to ROW at a price vector P * . ROW's economy is in equilibrium when:

Appendix B: Decomposition of import demand elasticity faced by exporters

The import demand faced by exporter i can be decomposed in the import demand of the world M W minus the sum of exports of all countries, formally:

where M stands for imports, X for exports. Taking the derivative with respect to the price of the good P, we have:

Multiplying both sides by P/M W , we get:

The term is the import demand elasticity of the world . It can be approximated by the trade weighted sum of import demand elasticities as estimated by [START_REF] Kee | Import Demand Elasticities and Trade Distortions[END_REF].

We can then multiply both sides by

The left hand side is now the import demand elasticity of the ROW faced by country i : , .

Next, making use of the fact that the total imports of the world must be equal to the total exports of the world:

The third term collapses to a weighted sum of the export supply elasticities faced by the exporter .

Furthermore, the imports of the rest of the World coming from country i are exactly the same as the exports from that country i to the rest of the world:

Appendix C: Regressions results: Robustness checks


M Ferreboeuf

V Mariot

B Bessières

A Vasiljevic

Tania Attié-Bitach

S Collardeau

Stéphane Roche

Frédérique Magdinier

Jérôme Robin-Ducellier

P Rameau

DUX 4 and DUX4 downstream target genes are expressed in fetal FSHD muscles

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

P.16.2

The DUX4 promoter is expressed in FSHD-affected tissues L. Wallace, J. Liu, S. Garwick-Coppens, S. Guckes, S. Harper The Research Institute at Nationwide Children's Hospital, Center for Gene Therapy, Columbus, United States Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal dominant disorder with a 1 in 7500 incidence. Symptoms typically arise in young adulthood and most patients show clinical features before age 30. FSHD is most commonly characterized by progressive wasting and weakness of facial and shoulder-girdle muscles, although no consistent pattern of penetrance or severity exists, even within affected families. A hallmark characteristic of FSHD is asymmetrical muscle weakness. There are also non-muscular features including retinal vasculopathy and high frequency hearing loss. Several recent breakthroughs now support a model in which mis-expression of the myotoxic DUX4 gene is a primary pathogenic event underlying FSHD. We hypothesized that there was a direct correlation between DUX4 expression patterns and the involvement of selected muscles (and ear and retinal pathologies) in FSHD. In short, we proposed that if DUX4 over-expression is indeed an underlying pathogenic event in FSHD, it must be preferentially expressed in FSHDaffected regions. To test this hypothesis, we developed transgenic reporter mice containing a putative DUX4 promoter cloned upstream of GFP. We generated three separate lines of DUX4 promoter-GFP mice. We found the DUX4 promoter directed GFP expression in the face and limbs of newborn and adult mice, as well as multiple cell types in the retina. Essentially all other organs were GFP negative with a few exceptions including the pancreas and brain (cerebellum, olfactory bulb, and hippocampus). Strikingly, all lines showed asymmetrical expression and variable penetrance in all GFP-positive tissues, even within individual litters. We conclude that our mice faithfully recapitulate expected DUX4 expression patterns in regions of FSHD pathology, and further suggest the role of DUX4 as pathogenic insult in FSHD. We are now using a modified but analogous system to inducibly express DUX4. http://dx.doi:10.1016/j.nmd.2013.06.639 P.16.3 DUX 4 and DUX4 downstream target genes are expressed in fetal FSHD muscles M. Ferreboeuf 1 , V. Mariot 1 , B. Bessie `res 2 , A. Vasiljevic 3 , T. Attie

´-Bitach 2 , S. Collardeau 3 , S. Roche 4 , F. Magdinier 4 , J. Robin-Ducellier 5 , P. Rameau 6 , S. Whalen 7 , S. Sacconi 8 , V. Mouly 1 , G. Butler-Browne 1 , J. Dumonceaux The facio scapulo humeral dystrophy (FSHD) is the third most prevalent muscular dystrophy. The common clinical signs usually appear during the second decade of life but when the first molecular dysregulations occur is still unknown. Our aim was to determine whether molecular dysregulations can be identified during FSHD fetal muscle development. We compared 2 muscle biopsies coming from one FSHD fetus and the cells derived from these biopsies with biopsies and cells coming from control fetuses. We mainly focus on DUX4 isoform expression since the expression of DUX4 has been confirmed in both FSHD cells and biopsies by several laboratories.

We measured by qRT-PCR DUX4 isoforms expression in fetal FSDH myotubes treated or not with a shRNA directed against DUX4 mRNA. We also analyzed DUX4 downstream genes expression in myotubes and fetal or adult FSDH and control quadriceps biopsies.

We show that DUX4-FL is not expressed in control myotubes whereas it is expressed FSHD myotubes. Interestingly, DUX4-FL expression level is much lower in trapezius than in quadriceps myotubes which is confirmed by the level of expression of DUX4 downstream genes: We observed that TRIM43 and MBD3L2 are already overexpressed in FSHD fetal quadriceps biopsies, at similar levels at those observed in adult FSHD quadriceps biopsies.

These results indicate that molecular markers of the disease are already expressed during fetal life, raising the question as to the role of DUX4 in the onset and progression of FSHD. Among 67 neuromuscular patients searching for psychoanalysis treatment (in the Psychoanalysis Clinic, Human Genome Center), facioscapulohumeral (FSHD) patients constitute an important group. Ten patients with clinical course ranging for very mildly to severely affected have asked for treatment with complaints of depression to date. Two patients, L. and J., described below, both with a family history of FSHD whose diagnosis were confirmed by molecular analysis, illustrate the positive effect of such approach.

L., aged 45, father of three children was only mildly affected. He never told his family that he had a genetic disorder. When his younger son started to show clinical signs of FSHD he found out he could not hide it any more but did not know how to deal with this situation. After 3 months of treatment he had not only revealed the truth to his family but also had decided to launch a similar psychoanalysis approach in his home town. In his last visit he declared: "For the first time in my life I took off my shirt and enjoyed swimming in the ocean".

J., aged 31, was examined for the first time at the HGC when she was 20 years old. She referred that since she was 12 years-old she had difficulty raising her arms and she was never able to whistle. Currently, she has significant hypotonia, upper limbs proximal asymmetrical muscle weakness and atrophy, facial weakness (inability to whistle, smile and close the eyes), severe lumbar hyperlordosis, scapular winging and proximal lower limbs weakness. Her mother and other maternal relatives are also affected but less severely. After psychoanalysis treatment she abandoned her resignation "feeling" and rejected others compassion "feeling" towards her. Despite her severe body deformity she decided to pursue her dream to be a teacher and went back to college. Similarly to the first patient she is now not ashamed of her body and they found another way to cope with their own sexuality.

  http://dx.doi:10.1016/j.nmd.2013.06.640 P.16.4 Psychoanalysis impact to facioscapulohumeral (FSHD) patientsJ. Forbes 1 , T. Genesini 1 , C. Riolfi 1 , E. Macedo 2 , D. Ru ¨diger 2 , L. Lise 2 , A. Mouzat 2 , R.C.M. Pavanello 3 , M.Zatz 3 1 Human Genome Research Center -University of Sa ˜o Paulo and Institute of Lacanian Psychoanalysis -IPLA, Biosciences Institute, Sa ˜o Paulo, Brazil; 2 Human Genome Research Center -University of Sa ˜o Paulo and Institute of Lacanian Psychoanalysis -IPLA, Biosciences Institute, Sa ˜o Paulo, Brazil; 3 Human Genome Research Center-University of Sa ˜o Paulo, Biosciences Institute, Sa ˜o Paulo, Brazil

  http://dx.doi:10.1016/j.nmd.2013.06.641 P.16.5 Anxiety is responsible for altered sleep quality in Facio-Scapulo-Humeral Muscular Dystrophy (FSHD) L. Leclair-Visonneau 1 , A. Magot 2 , A. Tremblay 3 , X. Bruneau 3 , Y. Pereon 2

  1 1 Universite ´Pierre et Marie Curie, Paris, France; 2 Universite ´Paris Descartes, Paris, France; 3 CHU-Lyon, Bron, France; 4 Faculte ´de Me ´decine de la Timone, Marseille, France; 5 UT Southwestern Medical Center, Groupe hospitalier Pitie ´-Salpe ´trie `re, Paris, France; 8 Nice University Hospital, Nice, France

	Dallas,	United	States; 6 Institut	Gustave	Roussy,	Villejuif,
	France; 7


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Jaime De Melo
email: jaime.demelo@unige.ch

Jean-Marc Solleder
email: jean-marc.solleder@unige.ch

The EGA Negotiations: why they are important, why they are stalled, and challenges ahead*

Keywords:

Decade-long negotiations on the reduction of tariffs on Environmental Goods (EGs) at the Doha Round using a list approach to define EGs, failed to produce an agreement. In July 2014, 14 countries entered plurilateral negotiations under the ambit of the WTO. If successful, the resulting Environmental Goods Agreement (EGA) would have eliminated tariffs on a list of EGs. These negotiations broke down in December 2016. The chapter documents this episode and the mercantilistic behavior of negotiators that prevented agreement on an extended list of EGs, a requirement to conclude a meaningful outcome for the environment.

A conclusion of the EGA negotiations under the current narrow agenda focusing only on tariffs could help build trust to go further but would be insufficient to help mitigate climate change, even if a 'critical mass' were to be reached allowing extension of the tariff reductions to all WTO members. This is because average tariffs for the negotiating group are too low (1.5 percent). Extending the agenda to include Non-Tariff Barriers (NTBs) and Environmental Services (ESs) remains the acid test for an EGA to address meaningfully the climate change challenge. Reaching agreement on how to tackle NTBs and ESs will require delegating negotiating authority to 'independent' scientific experts and probably modifying WTO rules.

* This paper The authors thank the French government for financial support under ANR-LABX-14-01.