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This study examined the factors influencing trade credits allowed by small and medium-sized enterprises (SMEs) in Nigeria. The study employed secondary data collected on trade credits and firm-specific factors from the audited annual reports and accounts of 34 non-financial quoted firms and macroeconomic variables, collected from the Statistical Bulletin of the Central Bank of Nigeria, over the years 1999-2012. The study used inferential statistics as well as econometric tools to analyze the data. The study found that accounts receivable (TRC) followed an autoregressive process after two periods hence; dynamic panel data estimation (Generalized Method of Moments) technique was used. While there was significant positive effect of size, trade credit received (accounts payable) and gross domestic product on trade credits allowed (accounts receivable), significant negative effect of cash flows, sales growth and industry was found. The study concluded that both the firm-specific and macroeconomic factors are important in explaining changes in the trade credits allowed by quoted SMEs in Nigeria.

Keywords: Trade credits allowed, firm-specific factors, macroeconomic factors, SMEs

  • Introduction

An enterprise can finance its activities through bank loans and advances, debentures,

bonds and leases, which are (most of the time) long term in nature. However, due to stringent conditions, formalities and procedures involved in obtaining them, these formal sources of finance seem unattractive to small and medium-sized enterprises (SMEs). The terrain of many economies is also constraining to SMEs that banks’ focus is on blue chip companies for lending purposes (Anaro, 2010). The enterprises therefore rely more on informal sources such as trade credits and retained profits for finances (Atanda, 2010).

There had been an increasing research focus on the factors responsible for the use of trade credits by non-financial firms. However, Frank & Goyal (2009) argued that the factors that influence trade credit financing remain indefinable even though there is a lot of theoretical literature and decades of empirical evidence. This means that the determinants of trade credits will be of continued interest to business finance scholars and managers due to changes in the features that characterize the economies of both developed and developing countries.

According to Li (2011), determinants of trade credits can be categorized into firm-specific and macroeconomic factors. Evidence abounds in the literature on the effects of product quality, firm size, firm age, industry and several other firm-specific factors on trade credits (Akinlo, 2012; Joeveer, 2013 and Kwenda & Holden, 2014). With the exception of Akinlo (2012) and few others on Nigerian firms, most of the studies were on foreign economies like USA (Petersen & Rajan, 1997), Europe (Garcia-Teruel & Martinez-Solano, 2010) and Asia (Ono, 2001). Besides, those that used data on Nigerian firms concentrated on large companies and consensus is lacking on the number of factors that influence trade credit use.

Demirguc-Kunt & Maksimovic (2001) commented that it is out of control of firms to improve macroeconomic factors such as monetary policy and gross domestic product. This might be the reason why many studies ignored this category of factors in the models used to capture the determinants of trade credits. However, examining the impact of these factors will help to identify policy issues that should be improved upon to complement individual firm’s efforts at harnessing the potentials of trade credits. Besides, since SMEs operate in and interact with the environment, which is sometimes turbulent, identifying the variables that mould the environment and ascertaining how these variables influence firm operations is very important.

In addition, many past studies used methodology that allowed multiple firm-specific factors to be modeled as determinants of trade credit and employed ordinary least square (OLS) regression technique without testing for time series properties of data series. This had led to spurious regression coefficients being estimated, which limited the forecasting abilities of the models specified in the studies. In fact, most of the studies did not examine the process that generated trade credit series, which might have followed an autoregressive (AR) or moving average (MA) or a mixed process i.e. autoregressive moving average (ARMA). This would have allowed the authors to ascertain the dynamic nature of trade credits.

Though, there is a growing body of literature identifying the determinants of trade credits use, ample empirical evidence is relatively lacking on the influence of both the firm-specific and macroeconomic factors on trade credits of small firms in Nigeria. This study argued that there is need to improve the theoretical and analytical frameworks in two key areas: the two categories of determinants (firm-specific and macroeconomic factors) and the effect of these determinants on trade credits allowed by SMEs in Nigeria. Therefore, this study examined the influence of firm-specific and macroeconomic factors on trade credits allowed by quoted SMEs in Nigeria.

The approach adopted in this study was distinct from the previous ones in that it integrated both the controllable and non-controllable factors in a single equation model, used panel data of the Nigerian quoted SMEs and tested time series properties of variables using Box-Jenkins Q-statistic and unit root methods. The study also employed dynamic panel data analysis method in addition to pooled OLS, fixed effects and random effects regression commonly used to estimate the coefficients of the explanatory variables. Rather than entangling both the sully and demand side effects, this study use the supply side to interprete results to directly test theoretical arguments.


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