| Economic blocs have always been an interesting phenomenon.It is common knowledge that the grouping of several countries into one big institution helps foster growth for its members and bestow them a bigger bargaining power when it comes to promoting their own trade activities.While similar countries tend to make up these blocs,special cases happen when the reasoning behind this categorization is less due to similar structure and more about their rise to economic power.Following its 2009 inauguration summit,BRIC—an economic bloc consisting of Brazil,Russia,India,and China—became a formal institution in 2010.Now,seven years later,the economic bloc is showing signs of struggle largely in part of global recession and economic slowdown of its members.On the other hand,speaking strictly from the perspective of nominal GDP,BRIC members remain near,if not within,the top economies of the world.Some critics argue that BRIC was a case of chance rather than design;that suddenly grouping together what could be considered disparate countries do not hold much merit in both economic and political terms.Nevertheless,there are also those who believe that BRIC countries have more in common than one might think and is a potentially large enough force to finally challenge the economic domination currently held by the Western countries.The victor of this argument remains an interesting question yet to be answered by time,and further research.However,returning to the matter at hand,it is possible to look at other perspectives aside from nominal GDP to either reinforce the idea of how solid BRIC is as a group,or perhaps to dispel that notion instead.While it is understandable that many factors revolve around growth,one of the more interesting elements—perhaps due to its difficulty to fully explain in one way or another—is innovation.Innovation is becoming increasingly important to explain how countries can become more efficient in their production,thus resulting in a faster and more sustainable economic growth.As a research focus,innovation is mostly discussed using evidence from firm level or regional level,and rarely in country level—especially not in an international level.This paper aims to look at innovation in that much bigger of a scale,to try and see how they work in BRIC countries.Another aspect to consider is that while numerous papers have discussed predictions concerning the ascension of these countries to overtake some of the larger economic groups such as G7 or EU,not many have talked about the structure of the four countries making up BRIC itself.Consider that while there are many angles to look at what exactly economic structure of a country means,two basic broad categorizations can be made in regards to its economic activity:domestic and international.Another focus of this research is to look at the domestic side of things by analyzing intersectoral linkages of each member country.In layman’s terms,intersectoral linkages can be defined as how sectors or industries affect each other during their production process.In essence,the emphasis of this study then is to discuss how innovation correlates with the intersectoral linkages of the key sectors that all four countries share in common.The aim of the inclusion of innovation is to look at how these countries utilize innovation in terms of the domestic activity that are important for not only one,but all of these countries,and whether they share similarities or differences in this particular aspect.Since this study is one of correlation,it is quantitative in nature.In this study,the author used secondary data sources available in the form of online data banks with credible qualifications.Data from these banks are then compiled and processed using several steps to properly correlate both elements.First,innovation is quantified as the number of patents published every year coming from the respective countries.While it is not necessarily without drawbacks,patents can be considered a hallmark of innovation considering it is the output of the research and development process,and since the ones that matter in this study belong to the specific country,it can then be used to represent innovation in this research.Data for patents are acquired from the World Intellectual Property Organization,which is one of the 17 specialized agencies of the United Nations.Their data is available online and frequently updated.Data collected for patents spanned from 2000 to 2014,which is 15 years’ worth of data.Secondly,the numbers for intersectoral linkages in a certain country can be estimated by using the national input-output tables of that country.There are many options to find IO tables online and one can refer to OECD or Eora MRIO,but in this instance the author chose to use the World Input-Output Database instead.The decision was made considering the global scale,robustness,and completeness of data provided—as well as its international reputation.Data collected for the national input-output tables also spanned from 2000 to 2014 for Brazil,Russia,India,and China.The actual technical aspect for the data processing itself is a little more complex.In order to correlate the patent data and the intersectoral linkages,first the intersectoral linkages numbers need to be calculated based on the input-output tables.The author computed the intersectoral linkages numbers using two different methods,which are the Chenery-Watanabe and Rasmussen methods.Each of this method yielded both backward and forward linkage numbers that,when combined,determined the key sectors in the domestic activity of a country.This process is done on all 56 industries available on the national input-output tables from 2000 to 2014,and the resulting information was then compiled into a time-series table.Key sectors that are the same in all four countries are taken out and given higher attention for the correlation process up next.Once this is done,the next issue to deal with is the patent numbers.Considering that the oldest patent data is from the year 2000,the author decided to start with the year 2005 to give the patents a 5-year accumulation time since older patents can still be utilized for more modern production.By giving the patents a 5-year head start,the patents can better reflect how they were being utilized in the production activity.Another problem with the patent data is that it is categorized using the IPC classification while the national input-output tablenumbers used the ISIC revision 4.This meant that both datasets do not speak the same language,and cannot be compared outright.Currently there is no concordance table aside from a relatively out-of-date table comparing IPC and ISIC revision 2,which is not useful for this study.As a result,the author had to concur both categories manually,strictly limiting the patent data to the ones already published by each country using standards that were already set in a previous paper attempting the same concordance process.Once all the patents are categorized in the ISIC revision 4,the author then proceeded to correlate both datasets from the year 2005 to 2014 to arrive at the end result for each country.It is important to note that in this process,several industries from the initial 56 are excluded since the patents do not belong within those categories—only the industries where the patents are included count into the correlation process.Finally,key sectors that the four countries share in common are taken out from the remaining industries to highlight the result of the correlation.Several conclusions can be drawn from the data analysis.To begin with,the intersectoral linkages analysis show that these four countries share very few similar key sectors within the categories where the patents belong—six sectors in total.When it comes to the numbers along the years,these countries also do not follow the same trend.China and Brazil,in particular,have completely opposite direction with the former having a rising intersectoral linkage and the latter a steady decrease instead.Russia and India has slightly more in common,although Russia has an upward tick while India downwards.Since the data for patents are used in an accumulative manner,i.e.patents in the previous year count towards the present year,the result becomes quite obvious:China has the highest correlation number,followed by Russia,then India,and Brazil at the last place.This leads to another conclusion:all four countries utilize patents differently when it comes to domestic activity.Another look at the patent data led the author to believe that number of patents also matter,considering that Brazil has the smallest number of patents,Russia and India having slightly different amount,and China the most patents.Also,several additional perspectives were added for the sake of curiosity—GDP and R&D expenditure comes to mind—but the overall conclusion remained the same.There were several limitations in this research,however,as it did not take into account the import numbers available in the input-output table.More methods can also be used to better analyze the intersectoral linkages in addition to the two methods employed in this study,such as the extraction methods.At present,there is little study or research in available literature tackling on innovation and how they relate to intersectoral linkages in an international scale.This research contributes to that gap as a different perspective on how one can analyze whether innovation and domestic economy relate in an economic bloc of what are presumably similar countries. |
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