ON LINKING COUNTRY MODELS THROUGH BILATERAL

Transcription

1 ON LINKING COUNTRY MODELS THROUGH BILATERAL INTERNATIONAL TRADE FLOWS. Data and modelling equations Rossella Bardazzi, Leonardo Ghezzi XII INFORUM World Conference Alexandria, US 1 st 5 th September, 2014

2 INTRODUCTION Links between economies in multi-country models act trough different channels: trade financial variables (e.g., interest rates) prices production factors In the past, trade links have been usually underestimated by economic literature while paying more attention to production factors and prices (see Whitley,1992) we decided to study international trade flows and to maintain / develop the BTM

3 WHY DID TRADE CAPTURE OUR ATTENTION? "Total Imports" "US (red) and China (blue)" "Total Imports" "GER (red), FRA (blue), and ITA (green)" TOTAL IMPORT TOTAL IMPORT x11 x x3 x2 x8

4 WHY DID TRADE CAPTURE OUR ATTENTION? Source: Baldwin (2009)

5 OUTLINE OF THE PRESENTATION i) ii) iii) iv) v) A selection of criteria for a taxonomy of applied trade models The INFORUM international system of models The new dataset with some preliminary descriptive results Future steps and some problems about data availability and specification of equations A message to the INFORUM group

6 I) CLASSIFICATION CRITERIA FOR APPLIED MODELS In this work we focus on international trade data and models. Some distinguished features: (a) the level of trade flows aggregation (b) the theoretical approach (c) the integration between country models. (d) the geographical coverage.

7 A taxonomy of selected applied models I) CLASSIFICATION CRITERIA FOR APPLIED MODELS Aggregation Theory Linkage Geography Project LINK Macro Traditional structural econometric model multilateral 100 Countries MULTIMOD Macro Augmented w/ Rational Expectations and Supply side features multilateral 21 countries + ROW INTERLINK Macro Augmented w/ Rational Expectations and Supply side features multilateral OECD countries + 3 groups (ROW) GTAP Multi-sector CGE (rapresentative agent's maxim.; Armington Assumption) bi-lateral Database with 129 Regions G-CUBE Multi-sector DSGE bi-lateral MSG2 Multi-sector DSGE bi-lateral Database with 129 Regions Database with 129 Regions GINFORS Multi-sector/Macro E3 - Multisectoral Econometric model bi-lateral OECD Countries + other major trading partners E3ME Multi-sector E3 - Multisectoral Econometric model multilateral 21 world regions FIDELIO Multi-sector Hybrid bi-lateral EU Countries

8 II) THE INFORUM INTERNATIONAL SYSTEM OF MODELS Main features of Bilateral Trade Model Type-I model Type-II model present i) The linking system of national models through BTM Multi-lateral flows; links trough World Prices Bi-lateral flows ii) a detailed disaggregation of commodity classification 120 sectors; 9 countries + 1 group 120 sectors; 13 countries + 3 groups iii) econometric estimation of import shares Relative prices Relative prices + relative capital stocks

9 Type-I model II) THE INFORUM INTERNATIONAL SYSTEM OF MODELS a solar system draws and radiates based upon OECD data prices used in the trade module were domestic prices the heart of the trade module is a squared trade share matrix M with as many rows as countries in the system, obtained using imports for each country. Its generic element is computed as:

10 II) THE INFORUM INTERNATIONAL SYSTEM OF MODELS Type-I model The basic equation to predict the evolution of M matrix is S i, j,t = Si, j,0 b i j P, i, j, t Pi,j,t is the relative price of the origin country i in market j; the relative price is a ratio between the domestic price in i (adjusted with the exchange rate), Pe,i,t, and the world price as seen from the country j of destination of the flows, Pw,j,t. Domestic prices are weighted average of the present price and the four years-before price. The system of weights varies among different commodities.

11 II) THE INFORUM INTERNATIONAL SYSTEM OF MODELS Type-II model In the 1990s, a significant change in the approach: Bilateral Trade Model (BTM) based upon Statistics Canada data prices used are domestic prices (tariffs) the share equation has been improved S i, j,t = β i, j,0 P P e, i, t w, j, t β i,j,1 K K e, i, t w, j, t β i,j,2 e β i,j,3 T t

12 III) THE NEW DATASET Main features: Data to describe international trade are collected by few international organizations EU - COMEXT ( ) and UN - COMTRADE ( ) for their high commodity disaggregation and also for country coverage The most common classifications used to describe international trade are the "Harmonized System" (HS) and the "Standard for International Trade Classification" (SITC) We decided to use a highly disaggregated level of data but we collapse into two-digits SITC classification because it s easier to control

13 III) THE NEW DATASET Two points of view: the perspective of the country of origin of the flows, considering data on exports; alternatively, the point of view of the country of destination, considering data on imports. We decided to use imports flows A new list of Countries has been adopted. Most of the included countries do not exhibit missing observations ( ). However, we do observe cases in which data either start later than 1999 or end before Moreover, some countries do display discontinuous series. The UN Comtrade database includes the first 90 importers (according to 2012 data this is more than 90% of the total value of imports).

14 III) THE NEW DATASET Comext database displays a mixed version of the SITC classification. We employ a bridge table to transform the SITC Rev 3 codes into the SITC Rev 4 ones (using up to 5 digit classifications) Most of the included countries switch from SITC Rev3 to SITC Rev4 in It is not always the case. Moreover, there are examples of countries presenting only a SITC Rev3 version of the database (e.g., Botswana). All flows are in current prices. Currency used is USDollar. Flows of EU-Comext dataset are converted from Euro to USDollar with the official exchange rates published by Eurostat.

15 III) THE NEW DATASET New features: Trade on Services is included in the dataset: the share of services in world trade reached 21% in 2009 EU - COMEXT and UN - COMTRADE as data sources (years ) The same classification in both sources The same perspective (country of destination) was used. Import flows were considered

16 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS Machinery in China 0.29 Power generating machinery China imports Japan SHARE 0.16 USA Germany 0.03 Korea tm47s11.12 tm47s13.12 tm47s14.12 tm47s3.12

17 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS Machinery in China General machinery China imports 0.27 Germany Japan SHARE 0.16 USA 0.05 Korea tm50s11.12 tm50s13.12 tm50s14.12 tm50s3.12

18 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS Machinery in China Specialized machinery China imports 0.37 Japan Germany SHARE 0.21 Korea 0.05 USA tm48s11.12 tm48s13.12 tm48s14.12 tm48s3.12

19 Technology in US IV) SOME PRELIMINARY DESCRIPTIVE RESULTS 0.62 office machinery in US from JAP, CHINA, and KOR 0.53 telecommunications in US from JAP, CHINA, and KOR SHARE 0.32 SHARE tm51s13.11 tm51s12.11 tm51s tm52s13.11 tm52s12.11 tm52s14.11

20 0.37 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS OIL from different Areas of the World Crude Oil, and refined products from Middle-east from Oil producers producers China SHARE 0.19 USA Italy 0.02 Germany tm23s16.3 tm23s16.8 tm23s16.11 tm23s16.12

21 0.38 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS OIL from different Areas of the World Crude Oil, and refined products from Russia Germany SHARE 0.19 Italy China 0.01 USA tm23s15.3 tm23s15.8 tm23s15.11 tm23s15.12

22 0.62 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS OIL from different Areas of the World Crude Oil, and refined products from Rest of the World Italy SHARE 0.46 China Germany 0.30 USA tm23s1.3 tm23s1.8 tm23s1.11 tm23s1.12

23 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS Fashion industry "Japan" Leather products "Oil Producers" Leather products SHARE 0.17 SHARE tm38s8.13 tm38s2.13 tm38s12.13 tm38s8.16 tm38s2.16 tm38s12.16 SHARE "United States of America" Leather products Green China Red Italy Blue - France 0.02 tm38s8.11 tm38s2.11 tm38s12.11

24 IV) SOME PRELIMINARY DESCRIPTIVE RESULTS Fashion industry 13 "Japan" Clothes and clothing accessories 16 "Oil Producers" Clothes and clothing accessories SHARE 0.42 SHARE tm59s8.13 tm59s2.13 tm59s "Russia" Clothes and clothing accessories tm59s8.16 tm59s2.16 tm59s12.16 SHARE 0.27 Green China Red Italy Blue - France 0.01 tm59s8.15 tm59s2.15 tm59s12.15

25 IV) A MESSAGE TO ALL INFORUM MEMBERS ask not what BTM can do for you; ask what you can do for BTM

26 IV) A MESSAGE TO ALL INFORUM MEMBERS Time series of investment by investing sectors (or capital stock by owner sectors) Time series of exports prices by sectors (or domestic production prices by sectors) Time series of exports and imports (total) from National Accounts an updated INFORUM-type model (complete and running)

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28 Service Code Description 200 Total EBOPS Services Transportation Sea transport Passenger Freight Other Air transport Passenger Freight Other Other transport Passenger Freight Other Travel Business travel Personal travel Communications services Construction services Insurance services Financial services Computer and information services Royalties and license fees Other business services Personal, cultural, and recreational services Government services, n.i.e. We could sum all Transport services excluding passenger Transport which could be summed up to Travel services to estimate Tourism related services

29 Live animals Fertilizers (other than those of group 272) Meat Plastics in primary forms Dairy products Plastics in non-primary forms Fish Chemical materials and products, n.e.s Cereals Leather, leather manufactures, n.e.s., and dressed furskins Vegetables and fruit Rubber manufactures, n.e.s Sugars, and honey Cork and wood manufactures Coffee, tea, cocoa, spices Paper Feeding stuff for animals Textile yarn, fabrics Miscellaneous edible products Non-metallic mineral manufactures, n.e.s Beverages Iron and steel Tobacco Non-ferrous metals Hides, skins and furskins, raw Manufactures of metals, n.e.s Oil-seeds and oleaginous fruits Power-generating machinery and equipment Crude rubber Machinery specialized Cork and wood Metalworking machinery Pulp and waste paper General industrial machinery and equipment, n.e.s., Textile fibres (other than wool) Office machines Crude fertilizers,and minerals (excluding coal, petroleum) Telecommunications Metalliferous ores and metal scrap Electrical machinery Crude animal and vegetable materials, n.e.s Road vehicles Coal, coke and briquettes Other transport equipment Petroleum,and related materials Prefabricated buildings; sanitary, plumbing, heating and lighting Gas Furniture Electric current Travel goods, handbags and similar containers Animal oils and fats Articles of apparel and clothing accessories Fixed vegetable fats and oils Footwear Animal or vegetable fats and oils, waxes Professional, scientific and controlling instruments Organic chemicals Photographic apparatus Inorganic chemicals Miscellaneous manufactured articles, n.e.s Dyeing, tanning and colouring materials Special transactions Medicinal and pharmaceutical products Coin (other than gold coin), not being legal tender Essential oils and resinoids and perfume materials; toilet, po Gold, non-monetary (excluding gold ores and concentrates)

30 EU Other Countries EU data from COMEXT data from COMEXT - imports - exports - exports Other Countries Data from Comext - imports no data from COMEXT

31 #1 Rest of the World, #2 France, #3 Germany, #4 United Kingdom, #5 Spain, #6 Austria, #7 Belgium, #8 Italy, #9 Canada, #10 Mexico, #11 US, #12 China, #13 Japan, #14 Korea, #15 Russia, #16 Middle-East Oil producers, #17 Rest of the Eurozone, #18 Rest of the EU28 Ordered Country list * Overseas territories are considered as part of the Main Country (UK, France, China,...) and so imports/exports flows are considered interregional transactions and not included in this dataset.

32 8 "Italy" "Gas" 0.82 SHARE tm24s15.8 tm24s1.8