Table − 1 presents the results of the goods sector for OECD countries for the period of 2007 to 2017 by using the Pseudo Maximum Likelihood Method (PPML), whereas Table-2 exhibits the results of the services sector for OECD countries using the same method and timeline. Column 1 represents the listed variables in both tables. We choose to use specific gaps to find the impact of any changes over the years for both sectors. This study includes both exporter-year and importer-year fixed effects.
To estimate McFadden's (2021) Pseudo R squared, this paper uses the following formula.
The log-likelihood of the intercept model and the log-likelihood of the full model are the total sum of squares and the sum of squared errors, respectively. The proportion of the likelihoods recommends the extent of an upgrade over the intercept model proposed by the full model. A likelihood varies from 0 to 1. If a model consists of a smaller likelihood, then there will be a substantial magnitude provided by the log of the likelihood compared to the log of a more likely model. Hence, a slight proportion of log-likelihoods specifies that the whole model is significantly preferable to the intercept model. When differentiating similar data between the two models, McFadden's for the model with the higher likelihood would be steeper.
Table-1: Panel Analysis, PPML, Goods Sector for OECD Countries.
Industry
|
Goods Sector
|
Year
|
2008
|
2010
|
2014
|
2017
|
Common Language
|
0.0333 ***
(0.010)
|
0.0538***
(0.009)
|
0.0237***
(0.0074)
|
0.0289***
(0.003)
|
Common Colony
|
0.2636***
(0.031)
|
0.3615***
(0.027)
|
0.1464***
(0.051)
|
0.0221
(0.014)
|
Time Difference
|
-0.0027***
(0.002)
|
-0.0148***
(0.002)
|
-0.0047***
(0.001)
|
5.50e-08**
(2.26e-08)
|
Entry Procedure to Business
|
-0.0174**
(0.008)
|
-0.0101***
(0.004)
|
0.007
(0.011)
|
7.502***
(1.230)
|
Entry Time to Business
|
0.0033***
(0.001)
|
0.0014*
(0.001)
|
0.0157***
(0.0054)
|
-7.860***
(1.3595)
|
EU Destination
|
-0.1212***
(0.032)
|
-0.0689**
(0.0296)
|
-0.0260
(0.0783)
|
3.251***
(0.5644)
|
Distance (log)
|
-0.0655***
(0.008)
|
-0.0141***
(0.003)
|
-0.0708***
(0.0036)
|
-0.0557***
(0.0033)
|
EXP YEAR FE
|
YES
|
YES
|
YES
|
YES
|
IMP YEAR FE
|
YES
|
YES
|
YES
|
YES
|
Log- Likelihood
|
-5159.765
|
-5153.382
|
-5100.068
|
-4542.326
|
Pseudo R-Squared
|
0.59
|
0.58
|
0.59
|
0.64
|
*, **,*** Statistically Significant at 10%, 5% and 1%; Standard Errors (Robust) in Parenthesis.
Table-2: Panel Analysis, PPML, Services Sector for OECD Countries.
Industry
|
Services Sector
|
Year
|
2008
|
2010
|
2014
|
2017
|
Common Language
|
0.0232**
(0.010)
|
0.0202
(0.013)
|
0.0149
(0.0155)
|
0.0116
(0.0139)
|
Common Colony
|
-0.0611**
(0.0253)
|
-0.0448
(0.0435)
|
0.1348*
(0.0698)
|
0.232***
(0.0345)
|
Time Difference
|
0.0040*
(0.002)
|
0.0050*
(0.0026)
|
0.0057*
(0.0032)
|
0.00045
(0.003)
|
Agreement PTA Services
|
0.0277***
(0.0089)
|
0.0210**
(0.010)
|
0.0513***
(0.0146)
|
0.0818***
(0.0147)
|
EU Destination
|
0.1305**
(0.0566)
|
0.1414*
(0.0756)
|
0.2062***
(0.0422)
|
0.549***
(0.0626)
|
Distance (log)
|
-0.0233***
(0.0076)
|
-0.0284***
(0.0092)
|
-0.064***
(0.0121)
|
-0.0352***
(0.0113)
|
EXP YEAR FE
|
YES
|
YES
|
YES
|
YES
|
IMP YEAR FE
|
YES
|
YES
|
YES
|
YES
|
Log- Likelihood
|
-5264.589
|
-5305.895
|
-4213.225
|
-4275.744
|
Pseudo R-Squared
|
0.56
|
0.60
|
0.59
|
0.56
|
*, **, *** Statistically Significant at 10%, 5% and 1%; Standard Errors (Robust) in Parenthesis.
If the primary language of OECD countries is the same, high trade in goods is evident. The effect of sharing a common language is positive, and it is statistically significant at a 1% level. Our result carries consistent with the work of Barattieri (2014), who found a similar result for a common language. His (Barattieri, 2014) finding suggests that sharing a common language has a positive impact on the manufacturing sector trade. Though his work did not find the relationship between sharing a common language and trade in the manufacturing industry statistically significant in 2008, my work finds that this relationship is statistically robust from 2008 to 2017 at the 1% significance level. Our finding is statistically substantial compared to Baratierri's analysis for sharing a common language, and the use of the panel data, I think, has produced better results in my paper. In the case of the services sector, sharing a common language will increase service trade among OECD nations. This paper resembles Baratierri's result until 2008 for sharing the same language between exporters and importers. However, after 2008, this relationship is positive but not statistically significant. This result is exciting and guides us to the conclusion that language is not a significant barrier to the services trade among the OECD countries to those OECD countries which do not share the same language.
The impact of the common colonizer (post-1945) is positive in the goods trade and is statistically significant at a 1% level till 2012. Despite the positive magnitude of the common colonizer, this is not statistically significant for 2017. On the other hand, the common colonizer of OECD countries has a negative impact till 2010 in the services sector. After 2010, it has a positive impact, and this is statistically significant. This finding simulates the finding of the work of Barattieri et al., (2016). If the time difference between exporter and importer is significant, there is likely to be less trade in the goods sector. The relationship between the time difference and the trade in goods is statistically significant. However, the time difference has a positive impact on the services trade.
Distance is the standard proxy to represent the trade cost in the gravity estimates. Distance between exporter and importer has a substantial impact on the goods trade, and it has a negative effect. The more considerable distance among OECD countries will discourage trade in both sectors, and this is statistically significant for both sectors. This finding supports the findings of Baratierri's work (Barattieri, 2014). Trade in goods and trade in services will be high among those nations who share a common border, and this makes sense because more considerable distance means high cost, which inevitably discourages trade.
If the exporting destination of the OECD countries is the EU, there will be less trade, and this is statistically significant until 2010. The trade in goods has increased in higher magnitudes in the goods sector after 2014 for the EU destination exports. On the contrary, if the destination of export is in the EU, an increase in trade in services is evident. This finding makes sense because the majority number of the OECD countries are members of the EU, and the lower trade was a consequence of the recession of 2008.
If the procedure to start a business is complex and consumes more time, there will be less trade among OECD countries in the goods sector. The lengthy procedure discourages trade among the OECD countries, and this is statistically significant till 2010. The effect of increasing the services trade through an agreement has had a positive and significant influence over the years for all OECD countries. If the destination is Europe to export, the increase in services trade is evident and statistically significant at a 1% level. This result is very realistic and resembles the finding of Barattieri et al., (2016) regarding the positive impact to increase the trade-in services through RTA, and it proves that any trade agreement will surely increase trade-in services among the interested nations.
The results of Pseudo R Squared in both tables (Table-1 & Table-2) are high, and these suggest that the models are a good fit, indeed. McFadden (1979) wrote in Chap. 15 titled "Quantitative Methods for Analyzing Travel Behaviour on Individuals: Some Recent Developments" where he mentioned that McFadden's Pseudo \({R}^{2}\) is "Excllent Fit" if it ranges from 0.2–0.4.
Figure-3 provides trends for the goods sector for four English-speaking countries (Australia, Canada, Great Britain and the US). Despite a negative trend until 2013 in the goods sector, the figure shows that Australia has followed a smooth path of improvement in the goods sector from 2013 to 2017. CHB index line represents that Australia has been consistent with its goods sector, and It never went down from previous years' improvement in the goods sector. Though Canada, the USA, and the UK have followed the same trend with ups and downs, the USA went down in higher magnitudes from 2010 to 2012 and has stepped up rapidly from 2013 in higher amplitudes as well. The improvement compared to the previous year's performance in the goods sector of Canada has not gone down in higher magnitudes than that of the UK's context. The stepper lines in 2017 suggest a critical fact that the USA and the UK have a more significant improvement in the goods sector compared to Canada and Australia. Thus, the exports of the USA and the UK increased significantly in 2017.
The same trend in the goods sector as in the services sector is evident in the US economy and the UK economy. Though both have almost the same kinds of higher magnitudes and stepped up in higher magnitudes, the USA has the highest amplitudes among all OECD countries in the service sector. Canada shows an improvement in the service sector from 2013 to 2017, albeit fluctuations from 2007 to 2013. Figure-3 and Figure-4 have the same trends in each of the sectors for these countries. These common trends provide evidence that the improvement in the goods sector is interlinked to the increase in the service sector at the country level for these countries. At the country level, the higher the trade in goods will have higher the trade in services. This finding supports the empirical works of Ariu and Arnold at the firm level only for these countries (Ariu, 2016) & (Arnold et al., 2011).
Moreover, the reduction rate of the CHB index is high in the goods sector compared to the services sector for the USA, which finds a similar result to What Barattieri (2014) found. However, the opposite case is evident after 2014. Both sectors are improving, and the goods sector is leading in the US economy. Austria, Poland (and Chile till 2012) have been consistent in improving both sectors together.
However, Belgium, Switzerland, Czech Republic, Germany, Denmark, Spain, Estonia, Finland, France, Greece, Hungary, Italy, Japan, Korea, Luxembourg, Latvia, Mexico, Netherlands, Norway, New Zealand, Portugal, Slovakia, Slovenia, and Turkey are those countries which have encountered with fluctuations over the years both in the goods sector as well as in the services sector. The trade pattern of OECD countries in both sectors is ambiguous over the years from 2007 to 2017.
Why does Canada have a service trade deficit?
According to Statistics Canada, the Canadian economy is heavily dependent on the service sector, and three out of four Canadians are employed in this sector. Despite this fact, Canada has a service trade deficit. The answer to this question is not readily apparent.
Let us compare Canada to the USA since the USA is the neighboring country sharing the same culture and language and the topmost service trade exporter in the World. Data suggests that the USA exports high-end services, whereas Canada does not. The number of workers working in the labour force is one of the reasons, we think. Even the figure below suggests this. The USA has almost eight times more persons in the labour force compared to Canada. Since the cost of labour is low in developing nations, the outsourcing industry can play a vital role here for Canada to increase its net export for high-end products. The USA is significantly utilizing this outsourcing industry to export high-end services that generate maximum revenue. What Baldwin & Forslid (2020) considers a thought piece for developing countries to export services directly. The open the door to skilled immigrants has made a difference for the USA. Canada recently started taking skilled immigrants, and the results are evident. The surprising fact is that the services sector is growing faster than the goods sector in Canada after 2015 as the Canadian government opened the door to skilled immigrants. Figure 6 shows the positive change in the services sector, and the gap of service trade deficit is shrinking. From Figure-6, it can be observed that Canada is performing well in the services sector after 2015, whereas the goods sector is fluctuating over the years.