Canadian Foreign Direct Investment in the U.S.: A Discrete Choice Analysis Approach
Bibliographic record
Abstract
Canadian researchers have traditionally been most concerned with incoming foreign direct investment (FDI). This preoccupation goes as far back as the late 1870s, when Canada's tariff policy resulted in a large inflow of foreign investment. The net inflow of FDI continued for the next century until the 1970s, when outward FDI by Canadian firms increased so rapidly that Canada became a net exporter of investment. Understanding the motivations behind Canadian investment abroad is important research goal. While previous studies have produced valuable results, their conclusions are often in conflict indicating that further research on FDI is necessary. For example, studies by Vertinsky and Raizada (1994) and Rao et al (1994) produce contradictory results on a number of factors. The main goal of this study is to determine why Canadian firms choose to invest in particular parts of the U.S. Do Canadian firms invest in the United States to gain greater access to large regional markets? Is it for tax purposes? Is it for skilled labour? Is it for low cost labour? This study attempts to answer questions such as these by analysing the spatial distribution of Canadian FDI in the United States from 1974 to 1994. A multinomial logit model is used to determine those factors that attract Canadian FDI to different U.S. states. Explaining FDI FDI is activity owned, organised, and controlled by a firm (or group of firms) outside its (or their) national boundaries. Specifically, Statistics Canada defines FDI as an investment that is made to acquire a lasting interest and effective voice in the management of enterprise operating in economy other than that of the (Statistics Canada 1997: 29). Statistics Canada suggests that to obtain effective voice or control, a direct investor must possess at least ten percent of the equity of enterprise (Statistics Canada 1997). Why do firms seek to obtain control of operations in a foreign country? Previous studies have attempted to increase our understanding of FDI through push and pull factors. Pull factors are the aspects of a foreign country that attract investment. On the other hand, push factors are elements of a home country that drive companies to seek investment opportunities elsewhere. Studies (Litvak and Maule 1981; Rugman 1987; Gandhi 1990; Knubley et al 1991; Meyer and Green 1996) repeatedly conclude that pull factors of foreign markets are more important than push factors in Canada. In particular, large foreign markets are attractive to Canadian investors. By examining the distribution of Canadian investment across states, we extend this argument by not only determining the relationship between Canadian FDI and large markets, but additional pull factors as well. Pull factors can be associated with John H. Dunning's (1977; 1991) Eclectic Paradigm. The principal hypothesis on which the Eclectic Paradigm is based suggests that a firm will engage in FDI if and when three conditions are satisfied. First, a firm must possess ownership advantages. These include such considerations as technology, know-how and brand names, and must be of sufficient value to overcome the risks of locating in unfamiliar business environment. Second, a firm's motivation to invest abroad depends not only on its ownership advantages, but also on its desire and ability to internalise these ownership advantages. Internalisation is the procedure by which a multinational firm preserves its ownership advantages by establishing a foreign subsidiary rather than leasing or selling its ownership advantages. The final aspect of the Eclectic Paradigm is locational advantages. Locational advantages determine which countries or regions host production by MNEs. Some areas appear more attractive to FDI than others. Eden (1993) groups locational advantages into three classes: economic, social and political. Economic advantages are based on area's endowment of labour, capital, natural resources, market and infrastructure. …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".