180 l REGIONAL INVESTMENT PIONEERS IN SOUTH ASIA
Notes 1. Price differences across geographic space over and above those related to transportation costs are thought to represent information costs. However, this approach works better for commodities without product or quality differentiation, a competitive environment (low markups), and low intranational trade costs. 2. In fact, the choice of foreign direct investment over an alternate engagement strategy may itself be driven by the risk of leakage of internal knowledge beyond firm boundaries. 3. Networks provide a kind of enforcement mechanism through sanctions, substituting for weak international enforcement of formal contracts. 4. The FDI entry decision is distinct from the FDI expansion decision (the extensive margin versus the intensive margin of FDI, respectively). In international trade, it has been shown that for the United States, it is the extensive margin—the entry and exit of exporter firms— that determines the variation in export volumes, as opposed to adjustments in export volumes by existing exporters, that is, the intensive margin (Bernard et al. 2010). No similar analysis has been applied to FDI entry and exit at the firm level, but a similar finding is assumed. In some countries, FDI in the form of retained earnings is important, which would imply that studying the investment expansion and retention question is also important. 5. The Z-score is calculated as (xd – mean)/standard deviation, where xd is the bilateral home score with respect to destination d, mean is the average home score across all destinations, and standard deviation measures the dispersion of home’s xd scores. A greater-than–1 standard deviation Z-score indicates a surplus and less than 1 indicates a deficit. The designation is driven by the score relative to both the mean and the standard deviation. Thus, if a country has scores that are very close for all countries (low standard deviation), small score differences may generate a knowledge surplus or deficit. To counter these situations, an additional absolute threshold (say, the overall population mean) could also be used in the classification. This implies that a score of 2.2, which is initially marked as a knowledge deficit (orange) based on the Z-score, would not be marked as such because it exceeds the population mean of 1.89. 6. The relatively high score for NER may reflect a bias in that the NER destination option followed directly after India in the survey, and respondents may have chosen the same score for both. 7. Similar perspectives are observed when respondents were asked about how well informed they were about rules and regulations in South Asian countries. The scores (not reported here) tend to be lower than those for knowledge connectivity, and Afghanistan and Pakistan had a knowledge deficit (low score) on Indian regulations. 8. The question was, “I would like to ask you a question about how much trust you have in people from various countries. For each, please tell me whether you have a lot of trust, some trust, not very much trust, or no trust at all.” 9. With eight categories of productivity, the impact of going from the bottom to the top is 3.2 (8 × 0.004) percent, compared with a 5 percent network effect for services investment. 10. Unfortunately, insufficient data on prior importing or the first year of importing from a country that has OFDI were collected to explore the role of importing in investment. In interviews, entrepreneurs were more familiar with their export market statistics than with
