TILMAâ€™s Bogus Logic
The Conference Board estimates that TILMA will add $4.8 billion to British Columbiaâ€™s economy. Even if one accepts the Conference Boardâ€™s assumptions, this figure should be $2.4 billion (as explained below).
However, some of these assumptions are highly questionable. The Conference Board argues,
â€œThe commercial services and wholesale and retail trade industries will benefit from [TILMA]. Increased trade liberalization will result in a more efficient allocation of resources between the two provinces, which in turn should lead to higher real incomes for residents of both provinces due to productivity advancements and lower prices as costs fall. Higher incomes will in turn lead to more spending, benefiting the commercial services and retail sectorsâ€ (see page 35).
Based on this notion that TILMAâ€™s supposed benefits for tradable sectors will have spin-offs for the whole economy, the Conference Board assigns a â€œ+1â€ to â€œwholesale and retail tradeâ€ and â€œcommercialâ€ for all regions. This assumption is quite significant since these two industries account for between 34% of employment, in northern British Columbia, and 47% of employment, in the Lower Mainland (see page 36).
Therefore, the â€œ+1â€ assigned to these industries in all regions accounts for around 0.4 of British Columbiaâ€™s 0.76 score. In other words, more thanÂ half of TILMAâ€™s projected benefits are based on assumptions about spin-offs to industries that barely engage in inter-provincial trade. Excluding these industries would reduce the agreementâ€™s estimated value for British Columbia toÂ $1.2 billion or less.
This projected gain for tradable industries mainly relates to lower transportation costs. Different trucking regulations are one of the few tangible examples of a â€œtrade barrierâ€ between Alberta and British Columbia. However, there must be simpler ways of harmonizing trucking regulations than a sweeping, comprehensive agreement like TILMA.
UPDATE (Jan. 8): Another interesting aspect of the Conference Boardâ€™s methodology is that, although the industrial and regional scores refer to effects on GDP, they are weighted by employment shares, a rough “proxy” forÂ GDP shares (see pages 3-4, 10 and 38).