How Does the Exchange Rate and Its Volatility Influence FDI to Canada? A Disaggregated Analysis
Abstract
:1. Introduction
2. Literature Review
2.1. Theoretical Literature
2.2. Empirical Literature
3. Methods
Data Sources and Econometric Models
- xi represents the value of the real effective exchange rate at each period;
- t denotes the window mean value of the effective exchange rate;
- t represents the total number of periods (t = 64);
- k denotes the length of the moving average window (k = 4).
- ECTt−1 is the lagged error correction term;
- λ is the ECT coefficient, which denotes the parameter reflecting the rate of correction for adjustments;
- p is the lag order for the dependent variable;
- q is the lag order for the independent variables.
4. Empirical Results and Discussion
4.1. Unit Root Tests
4.2. F-Bound and t-Test
4.3. Results of Aggregate FDI
4.4. Disaggregated Analysis: Results for FDI in Sectors
4.5. Results of the Alternative Model: Including Break Points
5. Conclusions and Policy Recommendations
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
1 | Our total FDI inflows to Canada are the sum of net FDI inflows in all sectors. The net FDI inflow for each sector is the difference between an increase in investment and a decrease in investment in that particular industry. |
2 | To overcome the issue of negative values and apply a logarithmic transformation, we attempted a moving average method to smooth the quarterly series; however, this approach did not work due to persistent negative values at the sector level, even after employing the moving average. Additionally, exploring the option of using the ratio of FDI inflows to outflows, as commonly practised in net import studies, also revealed similar challenges. In several cases, the data provided by Statistics Canada on FDI inflows and outflows exhibit negative values; therefore, the ratio remains negative. |
3 | To simply the effect of shocks, we also tested a single dummy combining Dum2008q4 and Dum2020q2 and expanded each shock for three quarters. |
4 | The results for the Phillip–Perron tests and first-differenced variables are available upon request. |
5 | The results of the t-statistics are in the same line with F-statistics. We only report F-statistic. t-statistics are available upon request. |
6 | In pursuit of enhancing the robustness of our analytical framework specifically for the effect of the volatility of REER, we embarked on a comprehensive examination as derived from a shifting window, from a four-quarter window to a five-quarter window. Our meticulous investigation revealed that this transition yielded no substantive changes at the sectoral level. Notably, the relationship between the volatility of REER and total FDI demonstrated a regrettably diminished explanatory potency, notably eroding the previously observed long-term statistical significance of this association. Intriguingly, this transition also engendered an unexpected attenuation in the previously established interdependence between LNGDP and total FDI. Furthermore, this transition instigated the emergence of autocorrelation and heteroscedasticity in residuals. |
7 | The test results for the Ramsey RESET are available upon request. |
8 | As part of the robustness check, using a single dummy variable based on shocks in 2008 (up to three quarters) and 2020 (up to three quarters) did not yield any significant differences in the estimated model outcome. |
9 | Results are available upon request. |
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Period | Total Net FDI | Energy and Mining (FDIENMI) | Manufacturing Industries (FDIMF) | Trade and Transport (FDITT) | Finance and Insurance (FDIFIN) | Management of Companies and Enterprises (FDIMNG) | Other Industries (FDIOTH) |
---|---|---|---|---|---|---|---|
2022Q1 | 17,978 | 3118 (17.35%) | 3223 (17.93%) | 77 (0.42%) | 908 (5.06%) | 10,673 (59.36%) | −22 (−0.12%) |
2022Q2 | 15,063 | 3650 (24.23%) | 5259 (34.91%) | 1563 (10.37%) | 3784 (25.12%) | −477 (−3.16%) | 1285 (8.53%) |
2022Q3 | 18,243 | 2232 (12.23%) | 5001 (27.41%) | 4083 (22.38%) | 1344 (7.37%) | 4179 (22.91%) | 1404 (7.70%) |
2022Q4 | 17,221 | 3188 (18.51%) | 3915 (22.73%) | 4311 (25.03%) | 4804 (27.90%) | −45 (−0.26%) | 1047 (6.07%) |
Variables | Test Statistic | p-Value | Stationary Status |
---|---|---|---|
FDITOTAL | −4.278 ** | 0.0034 | Stationary in level |
FDIENMI | −5.479 ** | 0.0000 | Stationary in level |
FDIMF | −5.238 ** | 0.0001 | Stationary in level |
FDITT | −4.412 ** | 0.0021 | Stationary in level |
FDIFIN | −4.659 ** | 0.0008 | Stationary in level |
FDIMNG | −6.530 ** | 0.0000 | Stationary in level |
FDIOTH | −5.683 ** | 0.0000 | Stationary in level |
LNGDP | −3.521 * | 0.0372 | Stationary in level |
LNOPEN | −2.688 | 0.2411 | Non-stationary in level |
LNREER | −2.431 | 0.3633 | Non-stationary in level |
LNVOL | −2.855 | 0.1774 | Non-stationary in level |
Critical values | α = 0.01, −4.124 | α = 0.05, −3.488 | α = 0.1, −3.173 |
Significance Level | [I(0)] L(10%) | [I(1)] L(10%) | [I(0)] L(5%) | [I(1)] L(5%) | [I(0)] L(2.5% | [I(1)]) L(2.5%) | [I(0)] L(1%) | [I(1)] L(1%) |
---|---|---|---|---|---|---|---|---|
Critical Values | 2.45 | 3.52 | 2.86 | 4.01 | 3.25 | 4.49 | 3.74 | 5.06 |
Equation | ARDL totalfdi lngdp lnopen lnreer lnvol, lags(1 0 1 1 0) ec btest | |||||||
F-Statistic | 7.994 | Result | Cointegration | |||||
Equation | ARDL fdienmi lngdp lnopen lnreer lnvol, lags(1 0 0 0 0) ec btest | |||||||
F-Statistic | 15.474 | Result | Cointegration | |||||
Equation | ARDL fdimf lngdp lnopen lnreer lnvol, lags(1 0 0 1 1) ec btest | |||||||
F-Statistic | 12.922 | Result | Cointegration | |||||
Equation | ARDL fditt lngdp lnopen lnreer lnvol, lags(1 0 0 1 0) ec btest | |||||||
F-Statistic | 10.148 | Result | Cointegration | |||||
Equation | ARDL fdifin lngdp lnopen lnreer lnvol, lags(1 0 0 1 1) ec btest | |||||||
F-Statistic | 10.780 | Result | Cointegration | |||||
Equation | ARDL fdimng lngdp lnopen lnreer lnvol, lags(1 0 0 0 1) ec btest | |||||||
F-Statistic | 14.224 | Result | Cointegration | |||||
Equation | ARDL fdioth lngdp lnopen lnreer lnvol, lags(1 1 0 0 1) ec btest | |||||||
F-Statistic | 14.923 | Result | Cointegration |
Variable | Coefficient | STD Error | T-Statistics | p-Value |
---|---|---|---|---|
ECT (−1) | −0.7958685 | 0.1283949 | −6.20 *** | 0.000 |
∆LNGDPt | 55,686.17 | 26,944 | 2.07 ** | 0.043 |
∆LNOPENt | −4058.413 | 48,260.94 | −0.08 | 0.933 |
∆LNREERt | 127,713.6 | 38,599.68 | 3.31 *** | 0.002 |
∆LNVOLt | 3880.538 | 2216.76 | 1.75 * | 0.086 |
Constant | −1,012,511 | 473,346.8 | −2.14 ** | 0.037 |
R2 | 0.5061 | Adjusted R2 | 0.4433 |
Variable | Coefficient | STD Error | T-Statistics | p-Value |
---|---|---|---|---|
LNGDPt−1 | 69,969.07 | 33,166.74 | 2.11 ** | 0.039 |
LNOPENt−1 | 87,694.13 | 37,910.07 | 2.31 ** | 0.024 |
LNREERt−1 | 65,256.19 | 24,877.63 | 2.62 ** | 0.011 |
LNVOLt−1 | 4875.854 | 2673.373 | 1.82 * | 0.074 |
Industry/Sector | Variable | Coefficient | STD Error | T-Statistics | p-Value |
---|---|---|---|---|---|
Energy and Mining (FDIENMI) | ECT (−1) | −1.121983 | 0.128131 | −8.76 *** | 0.000 |
∆LNGDPt | 20,290.28 | 13,950.67 | 1.45 | 0.151 | |
∆LNOPENt | −5445.683 | 15,652.36 | −0.35 | 0.729 | |
∆LNREERt | 26,247.58 | 10,300.41 | 2.55 ** | 0.014 | |
∆LNVOLt | 728.6559 | 1147.577 | 0.63 | 0.528 | |
Constant | −418,765.3 | 243,999.8 | −1.72 * | 0.092 | |
Overall Fit Measures | R2 | 0.5758 | Adjusted R2 | 0.5386 | |
Manufacturing Industries (FDIMF) | ECT (−1) | −0.9861048 | 0.1241345 | −7.94 *** | 0.000 |
∆LNGDPt | 14,048.73 | 18,372.53 | 0.76 | 0.448 | |
∆LNOPENt | 40,466.99 | 20,709.41 | 1.95 * | 0.056 | |
∆LNREERt | 74,235.58 | 25,149.04 | 2.95 *** | 0.005 | |
∆LNVOLt | 5552.736 | 2499.272.688 | 2.22 ** | 0.030 | |
Constant | −327,461.1 | 321,617.7 | −1.02 | 0.313 | |
Overall Fit Measures | R2 | 0.5889 | Adjusted R2 | 0.5366 | |
Trade and Transport (FDITT) | ECT (−1) | −0.9573658 | 0.1360218 | −7.04 *** | 0.000 |
∆LNGDPt | 5408.358 | 5773.209 | 0.94 | 0.353 | |
∆LNOPENt | 4385.413 | 6427.042 | 0.68 | 0.498 | |
∆LNREERt | 10,026.85 | 7832.668 | 1.28 | 0.206 | |
∆LNVOLt | 355.7322 | 479.5271 | 0.74 | 0.461 | |
Constant | −71,558.11 | 100375.6 | −0.71 | 0.479 | |
Overall Fit Measures | R2 | 0.4847 | Adjusted R2 | 0.4295 | |
Finance and Insurance (FDIFIN) | ECT (−1) | −1.013493 | 0.1396756 | −7.26 *** | 0.000 |
∆LNGDPt | 5078.019 | 5458.375 | 0.93 | 0.356 | |
∆LNOPENt | 4360.178 | 6079.007 | 0.72 | 0.476 | |
∆LNREERt | 14,094.35 | 7527.826 | 1.87 * | 0.066 | |
∆LNVOLt | 1459.764 | 771.5681 | 1.89 * | 0.064 | |
Constant | −80,405.18 | 95,216.37 | −0.84 | 0.402 | |
Overall Fit Measures | R2 | 0.4981 | Adjusted R2 | 0.4342 | |
Management of Companies and Enterprises (FDIMNG) | ECT (−1) | −1.070065 | 0.1310698 | −8.16 *** | 0.000 |
∆LNGDPt | 14,834.43 | 11,997.36 | 1.24 | 0.221 | |
∆LNOPENt | 10,718.42 | 13,390.37 | 0.80 | 0.427 | |
∆LNREERt | 4551.116 | 8690.936 | 0.52 | 0.603 | |
∆LNVOLt | −1018.394 | 1632.55 | −0.62 | 0.535 | |
Constant | −230,676.6 | 209,110.9.5 | −1.10 | 0.275 | |
Overall Fit Measures | R2 | 0.5595 | Adjusted R2 | 0.5123 | |
Other Industries (FDIOTH) | ECT (−1) | −1.134691 | 0.1320199 | −8.59 *** | 0.000 |
∆LNGDPt | −39,251.69 | 21,029.02 | −1.87 | 0.067 | |
∆LNOPENt | 24,425.95 | 12,235.82 | 2.00 * | 0.051 | |
∆LNREERt | −12,124.32 | 8183.108 | −1.48 | 0.144 | |
∆LNVOLt | 2045.576 | 1444.99 | 1.42 | 0.163 | |
Constant | 187,245.5 | 195,445.2 | 0.96 | 0.342 | |
Overall Fit Measures | R2 | 0.6157 | Adjusted R2 | 0.5668 |
Industry | Variable | Coefficient | STD Error | T-Statistics | p-Value |
---|---|---|---|---|---|
Energy and Mining (FDIENMI) | LNGDPt−1 | 18,084.31 | 12,371.58 | 1.46 | 0.149 |
LNOPENt−1 | 4853.625 | 13,967.01 | −0.35 | 0.729 | |
LNREERt−1 | 23,393.93 | 9008.224 | 2.60 ** | 0.012 | |
LNVOLt−1 | 649.436 | 1020.102 | 0.64 | 0.527 | |
Manufacturing Industries (FDIMF) | LNGDPt−1 | 14,246.69 | 18,571.79 | 0.77 | 0.446 |
LNOPENt−1 | 41,037.21 | 20,857.86 | 1.97 * | 0.054 | |
LNREERt−1 | 31,202.02 | 13,531.79 | 2.31 ** | 0.025 | |
LNVOLt−1 | 577.2225 | 1571.322 | 0.37 | 0.715 | |
Trade and Transport (FDITT) | LNGDPt−1 | 5649.208 | 5922.851 | 0.95 | 0.344 |
LNOPENt−1 | 4580.708 | 6696.589 | 0.68 | 0.497 | |
LNREERt−1 | −710.5176 | 4362.839 | −0.16 | 0.871 | |
LNVOLt−1 | 371.5739 | 490.9721 | 0.76 | 0.452 | |
Finance and Insurance (FDIFIN) | LNGDPt−1 | 5010.415 | 5357.417 | 0.94 | 0.354 |
LNOPENt−1 | 4302.13 | 5993.253 | 0.72 | 0.476 | |
LNREERt−1 | 2112.857 | 3901.402 | 0.54 | 0.590 | |
LNVOLt−1 | 353.1931 | 453.4005 | 0.78 | 0.439 | |
Management of Companies and Enterprises (FDIMNG) | LNGDPt−1 | 13,863.11 | 11,447.45 | 1.21 | 0.231 |
LNOPENt−1 | 10,016.6 | 12,485.86 | 0.80 | 0.426 | |
LNREERt−1 | 4253.121 | 8213.515 | 0.52 | 0.607 | |
LNVOLt−1 | 1520.994 | 969.5335 | 1.57 | 0.122 | |
Other Industries (FDIOTH) | LNGDPt−1 | −7024.7 | 9848.779 | −0.71 | 0.479 |
LNOPENt−1 | 21,526.52 | 10,527.39 | 2.04 ** | 0.046 | |
LNREERt−1 | −10,685.13 | 7093.479 | −1.51 | 0.138 | |
LNVOLt−1 | 56.44542 | 817.9582 | 0.07 | 0.945 |
Equation | Durbin–Watson d-Statistic | Breusch–Godfrey LM Test | Result |
---|---|---|---|
Energy and Mining (FDIENMI) | 2.006071 | Chi2 = 0.014 p-value = 0.9044 | No serial correlation |
Manufacturing Industries (FDIMF) | 2.114834 | Chi2 = 1.563 p-value = 0.2112 | No serial correlation |
Trade and Transport (FDITT) | 1.913474 | Chi2 = 0.967 p-value = 0.3254 | No serial correlation |
Finance and Insurance (FDIFIN) | 1.927294 | Chi2 = 0.144 p-value = 0.7047 | No serial correlation |
Management of Companies and Enterprises (FDIMNG) | 2.043401 | Chi2 = 0.752 p-value = 0.3858 | No serial correlation |
Other Industries (FDIOTH) | 1.987832 | Chi2 = 0.003 p-value = 0.9535 | No serial correlation |
Equation | White’s Test for Homoscedasticity | Result | Jarque–Bera Normality Test | Result |
---|---|---|---|---|
Energy and Mining (FDIENMI) | Chi2 (20) = 21.65 p-value = 0.3601 | Homoscedastic | Chi2 = 16.5 p-value = 0.00026 | Not Normally Distributed |
Manufacturing Industries (FDIMF) | Chi2 (35) = 50.18 p-value = 0.046 | Heteroscedastic | Chi2 = 113.1 p-value = 2.7 × 10−25 | Not Normally Distributed |
Trade and Transport (FDITT) | Chi2 (27) = 27.34 p-value = 0.4454 | Homoscedastic | Chi2 = 1.787 p-value = 0.4092 | Normally Distributed |
Finance and Insurance (FDIFIN) | Chi2 (35) = 35.68 p-value = 0.4361 | Homoscedastic | Chi2 = 2.416 p-value = 0.2988 | Normally Distributed |
Management of Companies and Enterprises (FDIMNG) | Chi2 (27) = 28.85 p-value = 0.3681 | Homoscedastic | Chi2 = 19.34 p-value = 6.3 × 10−5 | Not Normally Distributed |
Other Industries (FDIOTH) | Chi2 (35) = 39.32 p-value = 0.2826 | Homoscedastic | Chi2 = 676 p-value = 2 × 10−147 | Not Normally Distributed |
Variable | Coefficient | STD Error | T-Statistics | p-Value |
---|---|---|---|---|
ECT (−1) | −0.8197537 | 0.1254389 | −6.54 *** | 0.000 |
∆LNGDP t | 74,449.34 | 28,101.16 | 2.65 ** | 0.011 |
∆LNOPENt | 76,998.87 | 30,570.11 | 2.52 ** | 0.015 |
∆LNREERt | 156,240 | 41,417.96 | 3.77 *** | 0.000 |
∆LNVOLt | 5173.725 | 2334.7 | 2.22 ** | 0.031 |
dum2008q4t | 15,627.67 | 8592.137 | 1.82 * | 0.074 |
dum2020q2t | 17,380.83 | 8559.968 | 2.03 ** | 0.047 |
Constant | −1,341,135 | 493,876.3 | −2.72 *** | 0.009 |
R2 | 0.5399 | Adjusted R2 | 0.4717 |
Variable | Coefficient | STD Error | T-Statistics | p-Value |
---|---|---|---|---|
LNGDPt−1 | 90,819.16 | 33,526.86 | 2.71 *** | 0.009 |
LNOPENt−1 | 93,929.27 | 35,825.29 | 2.62 ** | 0.011 |
LNREERt−1 | 78,548.72 | 24,867.09 | 3.16 *** | 0.003 |
LNVOLt−1 | 6311.317 | 2707.447 | 2.33 ** | 0.024 |
dum2008q4t−1 | 19,063.86 | 10,635.04 | 1.79 * | 0.079 |
dum2020q2t−1 | 21,202.51 | 10,243.03 | 2.07 ** | 0.043 |
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Lajevardi, H.; Chowdhury, M. How Does the Exchange Rate and Its Volatility Influence FDI to Canada? A Disaggregated Analysis. J. Risk Financial Manag. 2024, 17, 88. https://doi.org/10.3390/jrfm17020088
Lajevardi H, Chowdhury M. How Does the Exchange Rate and Its Volatility Influence FDI to Canada? A Disaggregated Analysis. Journal of Risk and Financial Management. 2024; 17(2):88. https://doi.org/10.3390/jrfm17020088
Chicago/Turabian StyleLajevardi, Hooman, and Murshed Chowdhury. 2024. "How Does the Exchange Rate and Its Volatility Influence FDI to Canada? A Disaggregated Analysis" Journal of Risk and Financial Management 17, no. 2: 88. https://doi.org/10.3390/jrfm17020088