The effects of liquidity on inventory: Evidence form forestry subsector in Turkey

Yıl 2018, , 98 - 110, 26.10.2018

Ali Faruk Açıkgöz , Celal Demirkol Sudi Apak

https://doi.org/10.31195/ejejfs.458934

Cited By: 1

Öz

As a part of
Agriculture sector, forestry subsector is the main provider for the forestry
products industry which has been neglected in terms of short-term liabilities
and liquidity analysis. Liquidity is a function of the liabilities of the
businesses in the short-run and it is expected to consist much of trade credit
rather than bank credit. This study tries to reveal the long-term dependence of
the short-term inventories on cash and cash equivalents, short-term bank credit
used, and short-term accounts receivable as a percentage of short-term
liabilities in the forestry products subsector in Turkey. We analyze the sectoral three years averages of aggregate
balance sheet data in the long-term (1998 - 2016) and we depict that
inventories have correlations with cash and cash equivalents, short-term bank
credit and short-term accounts receivable and we also reveal that the sector’s
short-term liabilities have had a diminishing trend in the very long-run. After
introducing the model, we have run the linear regression of the model and we share
the robust results of the tests. The findings give evidence that inventories, which
are in fact the most illiquid part of the current assets, have bank credit
dependency as much as accounts receivable though decreasing liabilities in the
short-term. We therefore offer suggestions on the results for the forestry products
subsector so as to hedge against the potentially adverse liquidity conditions
in the near future. Each precaution held for a subsector will therefore help
the sustainability of the forestry and the agriculture sector as a whole and it
will also contribute as an example therein integrated especially with the
marketing strategies.

Anahtar Kelimeler

financial analysis, liquidity, inventory, bank credit, Forestry products subsector

Kaynakça

• Acikgoz, A.F., Apak, S., Erbay E.R. (2016). A long-term appraisal of the corporate liquidity dynamics in the selected nonfinancial sectors: Evidence from Turkey. International Balkan and Near Eastern Social Sciences (IBANESS) Conference Series. Faculty of Economics, October 28-30, 2016, University of St. Kliment Ohridski, Prilep – Republic of Macedonia, Proceedings Book: 101-107.
• Acikgoz, A.F., Apak, S., Demirkol, C. (2018). Non-cash components of net working capital: A long-term outlook of the agriculture sector in Turkey. International Balkan and Near Eastern Social Sciences (IBANESS) Conference Series. March 24-25, 2018, Tekirdag, Turkey, Proceedings Book Volume I: 64-72.
• Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In: Petrov, B.N. and Csaki, F., Eds., Second International Symposium on Information Theory, Budapest. 267-281.
• Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control. AC-19: 716–723.
• Akaike, H. (1979). A bayesian extension of the minimum AIC procedure of autoregressive model fitting. Biometrika 66 (2): 237-242.
• Aksu, B., Koc, K.H., Kurtoglu, A. (2011). The forest products industry in Turkey. African Journal of Business Management 5 (6): 2363-2369.
• Altman, E.I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance 23(4): 589-609.
• Altman, E.I., Narayan, P. (1997). An international survey of business failure classification models. Financial Markets, Institutions and Instruments 6(2): 1-57.
• Apak, S., Acikgoz, A.F., Erbay, E.R., Tuncer, G. (2016). Cash vs. net working capital as strategic tools for the long-term relation between bank credits and liquidity: inequalities in Turkey. Procedia-Social and Behavioral Sciences 235: 648-655.
• Bartlett, M.S. (1950). Tests of significance in factor analysis. British Journal of Mathematical and Statistical Psychology 3 (2): 77-85.
• Bayram, B.C., Akyuz, I., Ucuncu, T. (2015). The economic importance of Kastamonu Province in Turkish forest products industry in terms of some products. Kastamonu Univ., Journal of Forestry Faculty 15 (1): 90-97.
• Beaver, W.H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4 (Empirical Research in Accounting: Selected Studies) 71-111.
• Breusch, T.S. (1978). Testing for autocorrelation in dynamic linear models. Australian Economic Papers 17: 335-355.
• Breusch, T.S., Pagan, A.R. (1979). Simple test for heteroscedasticity and random coefficient variation. Econometrica (The Econometric Society) 47 (5): 1287-1294.
• Burkart, M., Ellingsen, T. (2004). In-kind finance: a theory of trade credit, The American Economic Review 94(3): 569-590.
• CBRT (Central Bank of the Republic of Turkey, 2018): CBRT Real Sector Statistics 1999-2017, Real Sector Balance Sheet Data and Archives for 1996–2016, last retrieved from http://www.tcmb.gov.tr on 12th of March 2018.
• Chong, B., Yi, H. (2011). Bank loans, trade credits, and borrower characteristics: Theory and empirical analysis. Asia-Pacific Journal of Financial Studies 40: 37-68.
• Cronbach, L.J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16: 297-334.
• Cronbach, L.J. (2004). My current thoughts on coefficient alpha and successor procedures. Educational and Psychological Measurement 64, 391–418.
• Dasgupta, S., Li, E.X.N., Yan, D. (2014). Inventory behavior and financial constraints: theory and evidence (November 26, 2017). Asian Finance Association (AsianFA) 2014 Conference Paper; 27th Australasian Finance and Banking Conference 2014 Paper; Swedish House of Finance Research Paper No. 16-17. Last revised on 3 December 2017. Available at SSRN: https://ssrn.com/abstract=2395018
• Dickey, D.A., Fuller, W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74: 427-431.
• Dieter, M., Englert, H. (2007). Competitiveness in the global forest industry sector: an empirical study with special emphasis on Germany. Eur J Forest Res 126: 401–412.
• Durbin, J., Watson, G.S. (1950). Testing for serial correlation in least squares regression. Biometrika. 37: 409-428.
• Durbin, J. (1970). Testing for serial correlation in least squares regression when some of the regressors are lagged dependent variables. Econometrica 38: 4410-4421.
• Durbin, J., Watson, G.S. (1971). Testing for serial correlation in least squares regression III. Biometrika 58: 1-19.
• Engle, R.F., Granger, C.W.J. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica 55 (2): 251-276.
• Fisher, R.A. (1925). Statistical Methods for Research Workers, Oliver & Boyd., Edinburgh.
• Fisher, R.A. (1932). Statistical Methods for Research Workers, 4th Edition, Edinburgh: Oliver & Boyd.
• Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 32 (200): 675-701.
• Friedman, M. (1939). A correction: the use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association 34 (205): 109-109.
• Godfrey, L. (1978a). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica 46: 1293-1302.
• Godfrey, L. G. (1978b). Testing for multiplicative heteroscedasticity. Journal of Econometrics 8 227-236.
• Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37 (3): 424-438.
• Granger, C.W.J., Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics 2: 111-120.
• Hansen, E., Juslin, H. (2005). Marketing of forest products in a changing world. New Zealand Journal of Forestry Science 35 (2/3): 190-204.
• Henderson, J.E., Joshi, O., Tanger, S., Boby, L., Hubbard, W., Pelkki, M., Hughes, D.W., McConnell, T.E., Miller, W., Nowak, J., Becker, C., Adams, T., Altizer, C., Cantrell, R., Daystar, J., Jackson, B., Jeuck, J., Mehmood, S., Tappe, P. (2017). Standard procedures and methods for economic impact and contribution analysis in the forest products sector. Journal of Forestry 115 (2): 112–116.
• Im, K.S., Pesaran, M.H., Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics 115: 53-74.
• Istek, A., Ozsoylu, I., Kizilkaya, A. (2017). Turkish Wood Based Panel Sector Analysis. Journal of Bartin Faculty of Forestry 19(1): 132-138.
• Jarque, C. M., Bera, A.K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters 6: 255-259.
• Jarque, C. M., Bera, A.K. (1987). A test for normality of observations and regression residuals. International Statistical Review 55: 163-172.
• Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Econ. Dynamics and Control 12: 231-254.
• Johansen, S. (1995). Likelihood-based influence in cointegrated vector autoregressive models. Oxford University Press Oxford.
• Keefe, M. O., Yaghoubi, M. (2016). The influence of cash flow volatility on capital structure and the use of debt of different maturities. Journal of Corporate Finance 38: 18-36.
• Kutner, M. H., Nachtsheim, C. J., Neter, J., Li, W. (2005). Applied Linear Statistical Models. 5th edition, McGraw-Hill-Irwin, New York.
• Koulelis, P. (2016). Forest products consumption and trade deficit in Greece during the financial crisis: A quantitative statistical analysis. Open Journal of Business and Management 4: 258-265.
• Kupcak, V., Smida, Z. (2015). Forestry and wood sector and profitability development in the wood-processing industry of the Czech Republic. Journal of Forest Science 61 (6): 244-249.
• Levin, A., Lin, C.F., Chu, C. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics 108: 1-24.
• Li, Y., Zhang, D. (2014). Industrial timberland ownership and financial performance of US forest products companies. Forest Science 60(3): 569-578.
• Lutkepohl, H. (1991). Introduction to multiple time series analysis. Springer New York, USA.
• Lutkepohl, H. (2004). Vector autoregressive and vector error correction models, in H. Lutkepohl and M. Kratzig (eds), Applied Time Series Econometrics (86–158) Cambridge University Press, Cambridge, UK.
• MacKinnon, J. G., Haug, A., Michelis, L. (1999). Numerical distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics 14 (5): 563-577.
• Maksymets, O., Lonnstedt, L. (2015). Trends in markets for forest-based products and consequences for selected countries. Open Journal of Forestry 5: 697-710.
• Michalski, G. (2008). Operational risk in current assets investment decisions: Portfolio management approach in accounts receivable. Agric. Econ. – Czech 54(1): 12-19.
• Pearson, K. (1920). Notes on the history of correlation. Biometrika 13: 25-45.
• Pesaran, M.H., Shin, Y. (1998). An autoregressive distributed-lag modelling approach to cointegration analysis. Econometric Society Monographs 31: 371-413.
• Pesaran M.H., Shin Y., Smith R.J. (2000). Structural analysis of vector error correction models with exogenous I(1) variables. Journal of Econometrics 97: 293-343.
• Phillips, P.C.B., Perron, P. (1988). Testing for a unit root in time series regression,” Biometrika 75: 335-346.
• Ponikvar, N., Tajnikar, M., Pusnik, K. (2009). Performance ratios for managerial decision-making in a growing firm. Journal of Business Economics and Management 10(2): 109-120.
• Psillaki, M., Eleftheriou, K. (2015). Trade credit, bank credit, and flight to quality: evidence from French SMEs. Journal of Small Business Management 53(4): 1219-1240.
• Sims C.A. (1980): Macroeconomics and reality. Econometrica, 48(1): 1-48.
• Sohn, S.Y., Kim, Y.S. (2013). Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking. Small Business Economics 41: 931-943.
• Schwarz, G. (1978). Estimating the dimension of a model, Annals of Statistics 6: 461–464.
• Tukey, J.W. (1949). One Degree of Freedom for Non-Additivity. Biometrics 5: 232-242.
• Valimaki, H., Niskanen, A., Tervonen, K., Laurila, I. (2004). Indicators of innovativeness and enterprise competitiveness in the wood products industry in Finland. Scandinavian Journal of Forest Research 19 (sup5): 90-96.