CHƯƠNG 5 : KẾT LUẬN
5.3 Hướng nghiên cứu trong tương lai
Thứ nhất, do những hạn chế về số lượng mẫu nghiên cứu nên kết quả chưa thật sự phản ảnh một cách chính xác nhất, do đó các nghiên cứu sau này có nhiều lời thế hơn trong thu thập dữ liệu, có thể mở rộng kích thước mẫu lớn hơn sẽ cho tác động rõ ràng, đáng tin cậy hơn, từ đó xác định chính xác mức vốnjln chuyển tốijưu giúp nhà quản trị mang lạijhiệujquảjcaojnhấtjchojcông ty và lợi ích cho cổ đơng.
Thứ hai, có thể thêm các biến kinh tế vĩ mô và vi mô ảnh hưởng đến doanh thu, lợi nhuận của công ty như cấu trúc vốn, chính sách tài chính, biến động tỷ giá, tỷ lệ lạm phát, dòng tiền hoạt động…để đánh giá tồn diện mối quan hệjvới khả năngjsinh lời củajcơng ty trong cácjchu kỳ kinhjtế khác nhau.
6 DANH MỤC TÀI LIỆU THAM KHẢO
Danh mục tài liệu tham khảo Tiếng Việt
Nguyễn Thành Cả - Nguyễn Thị Ngọc Miên (2014), Kinh Tế Lượng, NXB Kinh Tế Thành Phố Hồ Chí Minh.
Phạm Trí Cao – Vũ Minh Châu (2009), Kinh tế lượng ứng dụng, NXB Lao Động Xã
Hội.
Từ Thị Kim Thoa – Nguyễn Thị Uyên Uyên, 2014. Mối quan hệ giữa quản trị vốn luân chuyển và khả năng sinh lời: Bằng chứng thực nghiệm ở Việt Nam: Tạp chí phát triển
và hội nhập. Số 14: trang 62-70
Trần Ngọc Thơ (2005), Tài chính doanh nghiệp hiện đại, NXB Thống Kê.
Danh mục tài liệu tham khảo tiếng Anh
Avci, E. (2018). "Effects Of 2008 Global Crisis On Working Capital And Profitability Of Turkish Manufacturing Companies." Inquiry Vol 3: 2303-7105.
Azadegan, A. And D. Pai (2008). "Industrial Awards As Manifests Of Business Performance: An Empirical Assessment." Journal Of Purchasing And Supply Management 14(3): 149-159.
Barber, B. M. And J. D. Lyon (1996). "Detecting Abnormal Operating Performance: The Empirical Power And Specification Of Test Statistics." Journal Of Financial Economics 41(3): 359-399.
Bora Ramiah, V., Y. Zhao And I. Moosa (2014). "Working Capital Management During The Global Financial Crisis: The Australian Experience." Qualitative Research In Financial Markets 6 (3): 332-351.
Chang-Soo, K., D. C. Mauer And A. E. Sherman (1998). "The Determinants Of Corporate Liquidity: Theory And Evidence." Journal Of Financial & Quantitative Analysis 33(3): 335-359.
D’mello, R., S. Krishnaswami And P. J. Larkin (2008). "Determinants Of Corporate Cash Holdings: Evidence From Spin-Offs." Journal Of Banking And Finance 32(7):
1209-1220.
Darush, Y. And Ö. Peter (2014). "The Impact Of Cash Conversion Cycle On Firm Profitability: An Empirical Study Based On Swedish Data." International Journal Of Managerial Finance (4): 442.
Deloof, M. (2003). "Does Working Capital Management Affect Profitability Of Belgian Firms?" Journal Of Business Finance & Accounting 30(3/4): 573-587.
Emilio, F., M. Michael, R. Lukasz And E. Bank Of (2012). "Understanding The Macroeconomic Effects Of Working Capital In The United Kingdom∗." Bank Of England Working Paper No. 422.
Enqvist, J., M. Graham And J. Nikkinen (2014). "The Impact Of Working Capital Management On Firm Profitability In Different Business Cycles: Evidence From Finland." Research In International Business And Finance 32: 36-49.
Gill, A., N. Biger And N. Mathur (2010). "The Relationship Between Working Capital Management And Profitability: Evidence From The United States." Business Economics Journal 10(1): 1-9.
Huynh Phuong, D. And J.-T. Su (2010). "The Relationship Between Working Capital Management And Profitability: A Vietnam Case." International Research Journal Of Finance And Economics (Issue 49): 59-67.
Jarrad, H. (1999). "Corporate Cash Reserves And Acquisitions." The Journal Of Finance 54(6): 1969.
Jose, M. L., C. Lancaster And J. L. Stevens (1996). "Corporate Returns And Cash Conversion Cycles." Journal Of Economics & Finance 20(1): 33.
Kasiran, F. W., N. A. Mohamad And O. Chin (2016). "Working Capital Management Efficiency: A Study On The Small Medium Enterprise In Malaysia." Procedia Economics And Finance 35: 297-303.
Khalil, J., I. Amjad, B. Kalim Ullah, K. Muhammad Arif And H. Mustansar (2019). "Determinants Of Corporate Cash Holdings In Tranquil And Turbulent Period: Evidence
From An Emerging Economy." Financial Innovation (1): 1.
Lazaridis, I. And D. Tryfonidis (2006). "Relationship Between Working Capital Management And Profitability Of Listed Companies In The Athens Stock Exchange." Journal Of Financial Management & Analysis 19 (1): 26-35.
Lourenỗo Garcia, J. F., F. V. Da Silva Martins And E. F. Moreira Brandão (2011). "The Impact Of Working Capital Management Upon Companies' Profitability: Evidence From European Companies." Working Papers (Fep) -- Universidade Do Porto (438): 1- 35.
Matías, Braun Borja, Larrain (2005). "Finance and the Business Cycle: International, Inter‐Industry Evidence" Journal of Finance, 2005, vol. 60, issue 3, 1097-1128
Mielcarz, P., D. Osiichuk And P. Wnuczak (2018). "Working Capital Management Through The Business Cycle: Evidence From The Corporate Sector In Poland." Contemporary Economics 12(2): 223-236.
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Tham khảo từ nguồn internet, website http://www.bvsc.com.vn http://www.cophieu68.vn http://eds.a.ebscohost.com/eds/search/ http://www.sciencedirect.com https://www.investopedia.com/terms/w/workingcapital.asp https://en.wikipedia.org/wiki/Working_capital https://www.investopedia.com/terms/e/economic-cycle.asp http://baochinhphu.vn/Thi-truong/Quy-mo-von-hoa-thi-truong-chung-khoan-Viet- Nam-dat-39-trieu-ty-dong/358840.vgp) https://finance.vietstock.vn/du-lieu-vi-mo https://www.imf.org/en/Countries/VNM#countrydata
7 PHỤ LỤC
8 1. Bảng thốngjkê mô tả
9 2. Ma trận hệjsố tương quanjtoàn bộ mẫu
10 3. Ma trận hệjsố tương quanjgiai đoạn kinh tế bình ổn
kurtosis 12.61989 9.233465 67.6936 127.4085 16.64093 74.50809 38.08665 2.004326 69.76139 8.649458 skewness 1.178473 1.864114 5.34708 8.168705 2.835434 6.270905 4.923266 -.126613 7.335898 2.026903 N 1625 1625 1625 1625 1625 1625 1625 1625 1625 1625 max .7836998 1.874581 3098.373 3081.762 1029.143 832.5012 33.15058 1.036593 52561.95 .6951308 p50 .0602842 .2147399 117.3485 65.76899 68.9282 25.51514 1.539296 .4908514 542.4709 .0707044 min -.4174269 -.1382346 -51.6801 0 0 0 .0453191 .0244001 1.21 .0002459 sd .0735824 .2018973 168.9061 146.6713 97.13736 49.46357 2.46099 .2156136 4081.843 .0996789 mean .0720835 .2695824 156.9225 103.0146 92.36892 38.49674 2.299115 .4723178 1612.771 .1018409 stats ROA GOI CCC AR INV AP CR Debt REV CASH . tabstat ROA GOI CCC AR INV AP CR Debt REV CASH, stat (mean sd min p50 max N skew kurto)
CASH -0.2882* -0.0457 1.0000 SALES 0.3142* 1.0000
Debt 1.0000
Debt SALES CASH
CASH 0.2874* 0.1979* -0.2156* -0.1774* -0.1901* -0.1631* 0.3008* SALES 0.0588* 0.1079* -0.2048* -0.2270* -0.0673* -0.1088* -0.2971* Debt -0.4558* -0.3106* 0.1041* 0.0783* 0.2159* 0.3005* -0.5938* CR 0.2331* 0.1114* 0.0311 0.0446 -0.1004* -0.1714* 1.0000 AP -0.2755* -0.2684* 0.4338* 0.5432* 0.4437* 1.0000 INV -0.2308* -0.2335* 0.6671* 0.2558* 1.0000 AR -0.2280* -0.3140* 0.8562* 1.0000 CCC -0.2502* -0.3286* 1.0000 GOI 0.5894* 1.0000 ROA 1.0000 ROA GOI CCC AR INV AP CR . pwcorr ROA GOI CCC AR INV AP CR Debt SALES CASH, star (0.05)
CASH -0.2562* 0.0136 1.0000 REV 0.0864* 1.0000
Debt 1.0000
Debt REV CASH
CASH 0.2677* 0.2115* -0.2469* -0.2044* -0.2102* -0.1723* 0.2629* REV 0.1995* 0.2632* -0.1577* -0.1337* -0.1131* -0.0689 -0.0836* Debt -0.4426* -0.3143* 0.0754 0.0323 0.2221* 0.3431* -0.6227* CR 0.2516* 0.0887* 0.1171* 0.1742* -0.1041* -0.1889* 1.0000 AP -0.2990* -0.3146* 0.3806* 0.4011* 0.5369* 1.0000 INV -0.2387* -0.2251* 0.7165* 0.2677* 1.0000 AR -0.2329* -0.4179* 0.8279* 1.0000 CCC -0.2519* -0.3797* 1.0000 GOI 0.6295* 1.0000 ROA 1.0000 ROA GOI CCC AR INV AP CR . pwcorr ROA GOI CCC AR INV AP CR Debt REV CASH, star (0.05)
11 4. Ma trận hệ sốjtương quanjgiai đoạn kinh tế suy thoái
12 5. Ma trận hệ sốjtương quanjgiai đoạn kinh tế bùng nổ
CASH -0.2913* -0.0290 1.0000 SALES 0.3653* 1.0000
Debt 1.0000
Debt SALES CASH
CASH 0.2832* 0.2363* -0.2452* -0.1835* -0.2204* -0.1678* 0.3042* SALES -0.0140 0.0965* -0.2049* -0.2288* -0.1160* -0.1446* -0.2750* Debt -0.4619* -0.3635* 0.1768* 0.0922* 0.2649* 0.3163* -0.6058* CR 0.2662* 0.1451* -0.0328 -0.0263 -0.0939* -0.2093* 1.0000 AP -0.3169* -0.3391* 0.5179* 0.5320* 0.5599* 1.0000 INV -0.2195* -0.2502* 0.8109* 0.3149* 1.0000 AR -0.2619* -0.4011* 0.7794* 1.0000 CCC -0.2593* -0.3716* 1.0000 GOI 0.6768* 1.0000 ROA 1.0000 ROA GOI CCC AR INV AP CR . pwcorr ROA GOI CCC AR INV AP CR Debt SALES CASH, star (0.05)
CASH -0.3250* -0.0965* 1.0000 SALES 0.2412* 1.0000
Debt 1.0000
Debt SALES CASH
CASH 0.3231* 0.2073* -0.1769* -0.1742* -0.1417* -0.1619* 0.3450* SALES 0.0209 0.0927* -0.1807* -0.2090* 0.0075 -0.0888* -0.2730* Debt -0.4723* -0.3446* 0.0891* 0.1058* 0.1812* 0.2712* -0.5775* CR 0.1967* 0.1027* 0.0100 0.0031 -0.1057* -0.1496* 1.0000 AP -0.2588* -0.2654* 0.4435* 0.6144* 0.3781* 1.0000 INV -0.2279* -0.1854* 0.5675* 0.3103* 1.0000 AR -0.2432* -0.2919* 0.9249* 1.0000 CCC -0.2485* -0.2794* 1.0000 GOI 0.5849* 1.0000 ROA 1.0000 ROA GOI CCC AR INV AP CR . pwcorr ROA GOI CCC AR INV AP CR Debt SALES CASH, star (0.05)
13 6. Kiểm định Hausman - Thước đo ROA
14 7. Kiểm định Breusch và Pagan - Thước đo ROA
Prob>chi2 = 0.5706 = 4.79
chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B) Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg d2CCC .0000342 .0000331 1.04e-06 2.74e-06 d1CCC .0000145 .0000133 1.13e-06 1.93e-06 d2 .0047012 .0056247 -.0009235 .0007354 d1 .0033356 .0038845 -.0005489 .0005024 SALES .0044684 .0068585 -.0023901 .0016928 Debt -.1419634 -.1531745 .0112111 .0065373 CR -.0000994 -.0001213 .0000219 .0001757 CCC -.0000909 -.0000895 -1.39e-06 5.20e-06 FE RE Difference S.E. (b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
consider scaling your variables so that the coefficients are on a similar expect, or there may be problems computing the test. Examine the output o Note: the rank of the differenced variance matrix (6) does not equal the number of . hausman FE RE Prob > chibar2 = 0.0000 chibar2(01) = 929.96 Test: Var(u) = 0 u .0012676 .0356027 e .0026849 .0518162 ROA .0054144 .0735824 Var sd = sqrt(Var) Estimated results:
ROA[code,t] = Xb + u[code] + e[code,t]
15 8. Kiểm định Hausman - Thước đo GOI
16 9. Kiểm định Breusch và Pagan - Thước đo GOI
Prob>chi2 = 0.1169 = 12.86
chi2(8) = (b-B)'[(V_b-V_B)^(-1)](b-B) Test: Ho: difference in coefficients not systematic
B = inconsistent under Ha, efficient under Ho; obtained from xtreg b = consistent under Ho and Ha; obtained from xtreg d2CCC -.000096 -.0000839 -.0000121 3.08e-06 d1CCC .000025 .0000243 7.25e-07 . d2 .1389066 .1380253 .0008813 .0009909 d1 .0039028 .0043907 -.0004879 .0003135 SALES .0129523 .0171587 -.0042064 .0029502 Debt -.2638552 -.2866386 .0227835 .0105437 CR -.0023519 -.002632 .0002801 .0002382 CCC -.0001148 -.0001365 .0000217 7.76e-06 FE2 RE2 Difference S.E.
(b) (B) (b-B) sqrt(diag(V_b-V_B)) Coefficients
. hausman FE2 RE2
Prob > chibar2 = 0.0000 chibar2(01) = 929.96 Test: Var(u) = 0 u .0012676 .0356027 e .0026849 .0518162 ROA .0054144 .0735824 Var sd = sqrt(Var) Estimated results:
ROA[code,t] = Xb + u[code] + e[code,t]
17 10. Kiểm địnhjphương saijthay đổi và tựjtương quan - Thước đo ROA
18 11. Kiểm địnhjphương sai thay đổi và tựjtương quan - Thước đo GOI
LM(Var(u)=0,lambda=0) = 1114.18 Pr>chi2(2) = 0.0000 Joint Test:
ALM(lambda=0) = 184.21 Pr>chi2(1) = 0.0000 Serial Correlation:
ALM(Var(u)=0) = 22.73 Pr>N(0,1) = 0.0000 Random Effects, One Sided:
ALM(Var(u)=0) = 516.56 Pr>chi2(1) = 0.0000 Random Effects, Two Sided:
Tests: u .0012676 .03560273 e .0026849 .05181622 ROA .0054144 .0735824 Var sd = sqrt(Var) Estimated results:
v[code,t] = lambda v[code,(t-1)] + e[code,t] ROA[code,t] = Xb + u[code] + v[code,t]
Tests for the error component model:
LM(Var(u)=0,lambda=0) = 2768.39 Pr>chi2(2) = 0.0000 Joint Test:
ALM(lambda=0) = 145.13 Pr>chi2(1) = 0.0000 Serial Correlation:
ALM(Var(u)=0) = 42.39 Pr>N(0,1) = 0.0000 Random Effects, One Sided:
ALM(Var(u)=0) = 1796.77 Pr>chi2(1) = 0.0000 Random Effects, Two Sided:
Tests: u .0156121 .12494849 e .0136369 .11677697 GOI .0407625 .2018973 Var sd = sqrt(Var) Estimated results:
v[code,t] = lambda v[code,(t-1)] + e[code,t] GOI[code,t] = Xb + u[code] + v[code,t]
Tests for the error component model: . xttest1
19 12. Kiểm định Đa cộng tuyến
20 13. Kết quả hồi quy bằng phương pháp REM có sử dụng Robust – Thước đo ROA
Mean VIF 1.35 CCC 1.10 0.912828 SALES 1.21 0.824024 d1 1.25 0.798465 d2 1.27 0.789195 CR 1.59 0.627495 Debt 1.67 0.598033 Variable VIF 1/VIF . vif
rho .32069885 (fraction of variance due to u_i)
sigma_e .05181622 sigma_u .03560273 _cons .0159217 .0614831 0.26 0.796 -.1045829 .1364264 d2CCC .0000331 .0000293 1.13 0.257 -.0000242 .0000905 d1CCC .0000133 .0000268 0.50 0.618 -.0000391 .0000658 d2 .0056247 .0054109 1.04 0.299 -.0049805 .01623 d1 .0038845 .0051794 0.75 0.453 -.0062669 .014036 SALES .0068585 .0031139 2.20 0.028 .0007554 .0129616 Debt -.1531745 .0177333 -8.64 0.000 -.1879311 -.1184179 CR -.0001213 .0009782 -0.12 0.901 -.0020386 .0017959 CCC -.0000895 .00003 -2.98 0.003 -.0001483 -.0000306 ROA Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust
(Std. Err. adjusted for 125 clusters in code) corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(8) = 165.66 overall = 0.2809 max = 13 between = 0.4629 avg = 13.0 R-sq: within = 0.1119 Obs per group: min = 13 Group variable: code Number of groups = 125 Random-effects GLS regression Number of obs = 1625 . xtreg ROA CCC CR Debt SALES d1 d2 d1CCC d2CCC, re robust
rho .3127695 (fraction of variance due to u_i)
sigma_e .05232621 sigma_u .03530045 _cons -.0249215 .0612283 -0.41 0.684 -.1449268 .0950838 d2AP .0000438 .000049 0.89 0.371 -.0000522 .0001398 d1AP -.0001117 .0000923 -1.21 0.226 -.0002927 .0000692 d2 .0117025 .0040304 2.90 0.004 .0038032 .0196019 d1 .0109015 .0049374 2.21 0.027 .0012243 .0205787 SALES .0083565 .0031203 2.68 0.007 .0022407 .0144722 Debt -.148902 .018143 -8.21 0.000 -.1844616 -.1133423 CR -.000686 .0009551 -0.72 0.473 -.0025579 .0011859 AP -.0001374 .00006 -2.29 0.022 -.000255 -.0000197 ROA Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust
(Std. Err. adjusted for 125 clusters in code) corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(8) = 163.31 overall = 0.2718 max = 13 between = 0.4686 avg = 13.0 R-sq: within = 0.0947 Obs per group: min = 13 Group variable: code Number of groups = 125 Random-effects GLS regression Number of obs = 1625 . xtreg ROA AP CR Debt SALES d1 d2 d1AP d2AP , re robust
rho .31308374 (fraction of variance due to u_i)
sigma_e .05192969 sigma_u .03505856 _cons .0124343 .0622588 0.20 0.842 -.1095906 .1344593 d2AR .0000427 .0000405 1.05 0.292 -.0000367 .000122 d1AR -.0000507 .0000399 -1.27 0.204 -.0001288 .0000275 d2 .0086253 .0050896 1.69 0.090 -.0013501 .0186006 d1 .0100877 .0049981 2.02 0.044 .0002916 .0198838 SALES .0068213 .0031559 2.16 0.031 .0006358 .0130067 Debt -.1543995 .0179242 -8.61 0.000 -.1895303 -.1192687 CR -.0002605 .0009563 -0.27 0.785 -.0021347 .0016137 AR -.0000945 .0000437 -2.16 0.030 -.00018 -8.92e-06 ROA Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust
(Std. Err. adjusted for 125 clusters in code) corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(8) = 167.43 overall = 0.2831 max = 13 between = 0.4729 avg = 13.0 R-sq: within = 0.1081 Obs per group: min = 13 Group variable: code Number of groups = 125 Random-effects GLS regression Number of obs = 1625 . xtreg ROA AR CR Debt SALES d1 d2 d1AR d2AR , re robust
rho .31428479 (fraction of variance due to u_i)
sigma_e .05209313 sigma_u .03526714 _cons -.0254864 .0601605 -0.42 0.672 -.1433987 .092426 d2INV -3.88e-06 .0000384 -0.10 0.919 -.0000791 .0000713 d1INV .0000584 .0000368 1.59 0.112 -.0000136 .0001305 d2 .0101506 .0045365 2.24 0.025 .0012591 .0190421 d1 .0014926 .0049413 0.30 0.763 -.0081921 .0111774 SALES .0087355 .0030398 2.87 0.004 .0027776 .0146934 Debt -.1527223 .0177678 -8.60 0.000 -.1875464 -.1178981 CR -.0005451 .0009788 -0.56 0.578 -.0024635 .0013732 INV -.0001071 .0000377 -2.84 0.005 -.000181 -.0000332 ROA Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust
(Std. Err. adjusted for 125 clusters in code) corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(8) = 145.92 overall = 0.2684 max = 13 between = 0.4493 avg = 13.0 R-sq: within = 0.1026 Obs per group: min = 13 Group variable: code Number of groups = 125 Random-effects GLS regression Number of obs = 1625 . xtreg ROA INV CR Debt SALES d1 d2 d1INV d2INV , re robust
rho .31557695 (fraction of variance due to u_i)
sigma_e .0518977 sigma_u .03524021 _cons -.0514822 .0586771 -0.88 0.380 -.1664872 .0635228 d2CASH .0178137 .0331457 0.54 0.591 -.0471506 .082778 d1CASH .0162146 .0263598 0.62 0.538 -.0354498 .0678789 d2 .0119702 .0043742 2.74 0.006 .0033969 .0205434 d1 .0057811 .004196 1.38 0.168 -.0024429 .0140052 SALES .0091692 .0029754 3.08 0.002 .0033375 .0150008 Debt -.1553982 .0174733 -8.89 0.000 -.1896452 -.1211512 CR -.0016794 .0009482 -1.77 0.077 -.0035377 .000179 CASH .0989858 .0216481 4.57 0.000 .0565563 .1414153 ROA Coef. Std. Err. z P>|z| [95% Conf. Interval] Robust
(Std. Err. adjusted for 125 clusters in code) corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 Wald chi2(8) = 168.95 overall = 0.2850 max = 13 between = 0.4779 avg = 13.0 R-sq: within = 0.1095 Obs per group: min = 13 Group variable: code Number of groups = 125 Random-effects GLS regression Number of obs = 1625 . xtreg ROA CASH CR Debt SALES d1 d2 d1CASH d2CASH , re robust