scholarly journals A new method for calculating mirror data asymmetry in international trade

2020 ◽  
Vol 11 (4) ◽  
pp. 637-656
Author(s):  
Iwona Markowicz ◽  
Paweł Baran

Research background: Some statistics are of a bilateral nature. This is how foreign trade data is organized. They are recorded both in the supplier and recipient countries, hence they are called mirror data. The data recorded at both trading partner countries are not the same for different reasons. Such differences between data on the same groups of transactions are often referred to as the asymmetry of mirror data. The information about the value of the flows of goods are of great importance in economic analyses and therefore their quality is particularly important. Purpose of the article: The aim of this paper is to present a new measure of data asymmetry ? the aggregated quantity index with value-based weights. Methods: The proposed measure combines the quantity and the value of turn-over in individual trade relations. Such a measure makes it possible to eliminate basic deficiencies in value-based measures, while considering the specificity of trade in individual countries. The proposed measure of data asymmetry was confronted with several measures present in the literature and previously used by the Authors. The numerical example uses Comext data on intra-Community trade in 2017 provided by Eurostat. Findings & Value added: The proposed measure performs better than all the previously used data asymmetry indices. It is to some extent immune to exchange rate differences and inconsistencies resulting from the inclusion of transport and insurance costs in the value of goods. In addition, it gives lower weights to unimportant trade directions than other data asymmetry indices. Since the new index has proved to be better than the measures previously used, it is worth applying to those trade relations where the data are not de-rived from customs documents, but from declarations made by businesses, as in the case of intra-Community trade.


2019 ◽  
Vol 11 (10) ◽  
pp. 2740 ◽  
Author(s):  
Myoung Shik Choi ◽  
Bongsuk Sung ◽  
Woo-Yong Song

This study investigates the role of value-added bilateral trade focused on global value chains to achieve sustainable economic development. Our findings address trade policy implications that help to mitigate the global imbalances and exchange rate conflicts. These policies are expected to provide a competitive advantage that can be crucial to the sustainability of free trade. We apply traditional trade models to the value-added framework to examine the effects on value-added trade. Empirically, we investigate the bilateral value-added trade for recent years. Our major findings are that currency devaluation has a positive effect on value-added exports but has a negative effect on gross exports because of the effect on intermediate goods trading dominating the effect on international trade, i.e., the effect on foreign content of intermediate imports dominating the effect on the domestic content of exports. The same effect applies to imports. Also, we confirm that foreign income has a positive effect on exports and value-added exports, and domestic income has a positive effect on imports and value-added imports. However, their effects on trade balance are not consistent. Our major findings imply that the analysis of value-added trade can best contribute to the sustainability of global free trade by considering trade policies as a result of reflecting the easing of the global imbalance and the exchange rate war.



2021 ◽  
Author(s):  
◽  
Karam Shaar

<p>The common theme of the three papers in this thesis is the focus on the impact of data choices on empirical research in Economics. Such choices can be about the source of data; should we source the data from country A or country B in a bilateral trade relation? Is there a way to reconcile the discrepancies in international trade data? In investigating the impact of exchange rate on trade, should we choose high-frequency or low-frequency data? What does the choice of a certain frequency imply for the econometric analysis? In assessing the impact of housing wealth on household consumption, what are the benefits of choosing household-level data? How can we take advantage of aggregate data on house prices to circumvent the endogeneity arising from household-specific confounding factors? This thesis shows that data choices can strongly affect our conclusions regarding several modern economic issues.  The first paper is titled ‘Reconciling International Trade Data.’ International trade data are filled with discrepancies–where two countries report different values of trade with each other. We develop an index for ranking countries’ data quality based on the following notion: the more a country’s reports on bilateral trade differ from the corresponding reports of its partners, the more likely it is a low-quality reporter. We calculate the comparative quality for each country’s imports and exports separately for every year from 1962 to 2016. We reconcile international trade data through picking the value reported by the country with higher quality in every bilateral flow. The findings include: (a) global trade was under-reported by roughly 5% over the past five years as countries with low data quality under-report both, their imports and exports; (b) erroneous reporting is prevalent among low-quality reporters; (c) importers’ data are less likely to be in error; (d) the level of development and corruption are possible determinants of trade data quality; (e) low-quality reporters are 14% more open to trade using reconciled data than using self-reported data (f) China tends to under-report its exports and over-report its imports, while there is only a small difference between US self-reported and reconciled data. The reconciled trade dataset is made freely available for future studies to use.  The second paper is titled ‘Why You Should Use High Frequency Data to Test the Impact of Exchange Rate on Trade.’ The paper suggests that testing the impact of exchange rate on trade should be done using high frequency data. Using different data frequencies for identical periods and specifications between the US and Canada, the paper shows that low frequency data suppresses and distorts the evidence of the impact of exchange rate on trade in the short-run and the long-run.  The third paper is titled: ‘Housing Leverage and Consumption Expenditure: Evidence from New Zealand Microdata.’ The paper investigates how household debt affects the marginal propensity to consume out of housing wealth. The paper uses New Zealand household-level data on spending, income, and debt over the period 2006–2016. The main empirical challenge is to identify exogenous variation in house prices to determine how consumption evolves with movements in household wealth. This identification problem is complicated by the presence of unobserved household characteristics that are correlated with housing wealth. The paper uses a detailed house sale dataset to derive local average house prices and use it as an instrument. The empirical results show that the estimated elasticity of consumption spending to housing wealth is about 0.22%. In dollar terms, the average marginal propensity to consume out of a one-dollar increase in housing wealth is around 2.2 cents. The empirical results confirm that household indebtedness, especially mortgage debt, acts as a drag on consumption spending, not only through the debt overhang channel, but also through influencing the collateral channel of the housing wealth effect.</p>



2021 ◽  
Author(s):  
◽  
Karam Shaar

<p>The common theme of the three papers in this thesis is the focus on the impact of data choices on empirical research in Economics. Such choices can be about the source of data; should we source the data from country A or country B in a bilateral trade relation? Is there a way to reconcile the discrepancies in international trade data? In investigating the impact of exchange rate on trade, should we choose high-frequency or low-frequency data? What does the choice of a certain frequency imply for the econometric analysis? In assessing the impact of housing wealth on household consumption, what are the benefits of choosing household-level data? How can we take advantage of aggregate data on house prices to circumvent the endogeneity arising from household-specific confounding factors? This thesis shows that data choices can strongly affect our conclusions regarding several modern economic issues.  The first paper is titled ‘Reconciling International Trade Data.’ International trade data are filled with discrepancies–where two countries report different values of trade with each other. We develop an index for ranking countries’ data quality based on the following notion: the more a country’s reports on bilateral trade differ from the corresponding reports of its partners, the more likely it is a low-quality reporter. We calculate the comparative quality for each country’s imports and exports separately for every year from 1962 to 2016. We reconcile international trade data through picking the value reported by the country with higher quality in every bilateral flow. The findings include: (a) global trade was under-reported by roughly 5% over the past five years as countries with low data quality under-report both, their imports and exports; (b) erroneous reporting is prevalent among low-quality reporters; (c) importers’ data are less likely to be in error; (d) the level of development and corruption are possible determinants of trade data quality; (e) low-quality reporters are 14% more open to trade using reconciled data than using self-reported data (f) China tends to under-report its exports and over-report its imports, while there is only a small difference between US self-reported and reconciled data. The reconciled trade dataset is made freely available for future studies to use.  The second paper is titled ‘Why You Should Use High Frequency Data to Test the Impact of Exchange Rate on Trade.’ The paper suggests that testing the impact of exchange rate on trade should be done using high frequency data. Using different data frequencies for identical periods and specifications between the US and Canada, the paper shows that low frequency data suppresses and distorts the evidence of the impact of exchange rate on trade in the short-run and the long-run.  The third paper is titled: ‘Housing Leverage and Consumption Expenditure: Evidence from New Zealand Microdata.’ The paper investigates how household debt affects the marginal propensity to consume out of housing wealth. The paper uses New Zealand household-level data on spending, income, and debt over the period 2006–2016. The main empirical challenge is to identify exogenous variation in house prices to determine how consumption evolves with movements in household wealth. This identification problem is complicated by the presence of unobserved household characteristics that are correlated with housing wealth. The paper uses a detailed house sale dataset to derive local average house prices and use it as an instrument. The empirical results show that the estimated elasticity of consumption spending to housing wealth is about 0.22%. In dollar terms, the average marginal propensity to consume out of a one-dollar increase in housing wealth is around 2.2 cents. The empirical results confirm that household indebtedness, especially mortgage debt, acts as a drag on consumption spending, not only through the debt overhang channel, but also through influencing the collateral channel of the housing wealth effect.</p>



2020 ◽  
pp. 52-62
Author(s):  
I.S. Smirnov

The article assessed the potential use of gravity models to test the impact of various socio-geographical factors on international and inter-regional trade. The potential of gravitational modeling was estimated based on testing the theory of Linder’s Country similarity theory on recent trade data. This theory was one of the key theories of international trade in the post-war period. The classical gravity model of international trade can be used to test the change in the importance of the country similarity factor over a certain time period. The gravity model will demonstrate more significant results compared to its classical version (excluding the country similarity factor) in the case of a positive effect of the similarity factor on the volume of bilateral trade between countries. The analysis of recent trade data allowed us to assess the extent of change in the country similarity factor over the past 70 years. This period was accompanied by high growth in international trade, as well as the involvement of developing countries in the international division of labor. Vigorous market competition for the production of industrial goods led to the fact that manufacturers were forced to cut costs by moving their main production capacities to developing countries, which significantly differ from them in their level of economic development. The country similarity factor has lost its significance in this new system of international trade relations. As a result, at present the country similarity factor is not a key factor explaining the volume of trade relations between different countries.





2019 ◽  
pp. 79-91 ◽  
Author(s):  
V. S. Nazarov ◽  
S. S. Lazaryan ◽  
I. V. Nikonov ◽  
A. I. Votinov

The article assesses the impact of various factors on the growth rate of international trade. Many experts interpreted the cross-border flows of goods decline against the backdrop of a growing global economy as an alarming sign that indicates a slowdown in the processes of globalization. To determine the reasons for the dynamics of international trade, the decompositions of its growth rate were carried out and allowed to single out the effect of the dollar exchange rate, the commodities prices and global value chains on the change in the volume of trade. As a result, it was discovered that the most part of the dynamics of international trade is due to fluctuations in the exchange rate of the dollar and prices for basic commodity groups. The negative contribution of trade within global value chains in 2014 was also revealed. During the investigated period (2000—2014), such a picture was observed only in the crisis periods, which may indicate the beginning of structural changes in the world trade.



2018 ◽  
Vol 1 (4) ◽  
pp. 9-18
Author(s):  
Rasulov Tulkin Sattarovich ◽  
Khushvaktov Kuvonchbek Ravshanovich

In today’s world of swiftly increasing global economy and continuously changing international trade laws and technology exchange rate plays a pivotal role in the production, price formation, export and import of agricultural products. For many years exchange rate as an integral part of agricultural economics has been ignored. The present study was intended to investigate exchange rate as an impacting factor on the agricultural production. It also considers the researches that have been carried about the impact of the exchange rate on prices and export of agricultural products, theirs analyses and how much impact it has in the situation of Uzbekistan.



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