商科代写|计量经济学代写Econometrics代考|A. López-Villavicencio and V. Mignon

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• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

商科代写|计量经济学代写Econometrics代考|Indicators of Globalization

Let us now describe our five indicators of globalization. First, at the aggregated and disaggregated levels, trade openness is defined as the sum of extra-EU exports and imports over GDP. Overall and disaggregated trade values are collected from the Comext database. Note that, according to our previous discussion (see Sect. 1), the sign of the ERPT coefficient can be positive or negative. Indeed, following Benigno and Faia (2016), $\theta^{C}$ should be positive and significant if we expect that higher trade openness implies that there are more foreign firms competing in the destination market. In this case, globalization affects the dynamics of imported inflation through its effect on ERPT into import prices, the rise in the share of foreign products in the domestic market increasing the pass-through degree. However, in case of strategic complementarity in setting prices, a foreign exporter does not want its price to deviate too far from its competitors. Thus, the foreign exporter’s price becomes more responsive to the prices of its competitors as its markup increases. As a consequence, it is optimal for a firm to vary its markup more and its price less in response to an exchange rate change. Accordingly, we should observe a reduction of the passthrough of exchange-rate changes to import prices with higher trade integration $\left(\theta^{C}\right.$ should be negative and significant).

Second, we also evaluate how China’s presence in total imports may have affected the pricing decisions of exporters from other countries. We, therefore, consider China’s imports share over total imports as well as China’s share in each SITC sector [see Marazzi et al. (2005)]. Our third global indicator is a measure of intraindustry trade. Here, the underlying hypothesis is that increasing levels of intraindustry trade reflect higher product differentiation with respect to foreign competitors. Indeed, as shown by Caves (1998), product differentiation leads to increasing levels of intra-industry trade among countries, providing opportunities to develop new market-niches. To test for this hypothesis, we employ the Grubel-Lloyd index of intra-industry trade $I I T$ [see Lipsey (1976)], which is computed as follows:
$$M I_{t}=2 \times \frac{\min \left(M_{t} ; X_{s}\right)}{\left(M_{t}+X_{t}\right)}$$
where $M$ denotes extra-EU imports, and $X$ stands for extra EU-exports (of each SITC sector in the disaggregated analysis) in the considered country. The index ranges between zero (no intra-industry trade) and one (perfect intra-industry trade), and captures the level of product heterogeneity and trade complementarity between each sector-country pair and the trading partners. We interpret an increase in intra-industry trade as an adjustment to trade liberalization. Indeed, as suggested by Colantone et al.

商科代写|计量经济学代写Econometrics代考|Descriptive Statistics

Tables 1 and 2 provide some descriptive statistics referring to our five different globalization indicators and their growth over the period under study. At the country level (Table 1), Belgium is the country displaying the highest degree of trade openness. However, the level of trade exposure is increasing everywhere, particularly in Germany in addition to Belgium. France is the less opened economy and is the country that exhibits the lowest trade exposure growth. At the industry level (Table 2 ), openness is relatively higher for chemicals and related products (SITC 5), machinery and transport equipment (SITC 7) and miscellaneous manufactured articles (SITC 8), and it has especially increased for animal and vegetable oils (SITC 4) in France and Germany and miscellaneous manufactured articles (SITC 8) in all countries.

Looking at the figures in Table 2 another trend seems to emerge: Chinese imports account for about $35 \%$ in miscellaneous manufactured articles and, while being much lower in other sectors such as chemicals, they have been increasing over time in all panels. This is particularly the case in machinery, even though the average tariff rate increased slightly over the period. Intra-industry trade, in turn, is very heterogeneous among the different sectors in the three countries but, as it is known in the literature, it tends to be higher for manufactured goods than for raw materials or primary goods [see, e.g., Deese (2016)]. Finally, it is interesting to note that intra-EU imports represent more than $70 \%$ in several sectors. However, regional trade has decreased in sectors such as manufacturing or chemicals (except in Germany).

商科代写|计量经济学代写Econometrics代考|Accounting for Globalization

To assess the role of globalization at the country level, Table 4 reports the estimation results of Eq. (2). We consider the five aforementioned indicators in favor of globalization, namely: (i) an increase in the degree of trade openness, (ii) a higher intra-industry trade, (iii) a higher presence of Chinese imports over total imports, (iv) lower import tariffs, and (v) higher intra-EU trade as a regional globalization measure.

As shown, the interactive effect between exchange rate changes and globalization is mostly non-significant. This means that an increase in product differentiation with respect to foreign competitors, in the share of products from China in total imports and in the share of intra-UE imports, as well as a decline in import tariffs do not contribute to explaining the ERPT to import prices, at least at the aggregate level. The sole significant interactive terms are obtained when considering growth in trade openness and intra-industry trade for Germany and a higher presence of Chinese imports over total imports in France, suggesting that globalization tends to slightly increase the ERPT degree. Regarding Germany, these findings can be related to the fact that the German economy has known an important rise in trade openness over the period under study, leading to greater competition. In line with the argument developed by Benigno and Faia (2016), this growing competition due to the increase in the share of foreign products pushes up the degree of ERPT. In other words, there is slight evidence that the impact of firms’ entry on pass-through outweighs the effect of markup adjustments at the intensive margin.

While overall evidence regarding the pass-through effect of global factors is quite weak, it is worth noticing that their impact can operate through other channels. For instance, as recalled by Marazzi and Sheets (2007), pricing decisions of exporters from other countries may have been affected by the efforts made to remain competitive against China. The Chinese economy has also proven its high capacity to win market share, making credible the threat of its potential competition and constraining other exporters from passing through exchange rate shocks. Besides and at a more general level, if there is heterogeneity prevailing at the industry level, results based on aggregated import prices present aggregation bias, suggesting the importance of assessing ERPT degree at the sectoral level with disaggregated data.

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