I. Introduction

From a global perspective, the non-financial corporate sector in advanced economies has begun to shift from a net borrower to a net lender in the 2000s. However, the rise in profits did not translate into higher investments, resulting in growing cash holdings of firms. Similar patterns are observed in ASEAN5 countries.² In the case of large profits, ASEAN5 firms have tended to increase net saving, as opposed to paying more dividends or increasing investment.

While similar, corporate saving behavior in ASEAN5 countries may have different underlying drivers than its counterpart in advanced economies. In advanced economies with deep financial markets, flexible exchange rates, and open capital accounts, the rise in corporate saving is largely driven the rise of tech firms. (Bates et al., 2009; Booth and Zhou, 2013; Begenau and Palazzo, 2017). In contrast, high-tech companies in most ASEAN5 economies are relatively young and have a much lower saving rate compared to high-tech firms in the U.S. (Figure A2). Separately, Indonesia, Malaysia, Philippines and Thailand have relatively less developed financial markets and a history of using a range of measures, including FXI and capital flow measures, to tackle external shocks. These aggregate characteristics are likely to help explain corporate saving behavior of ASEAN5 countries.

Indeed, in countries with less developed financial markets, corporates are more likely to face binding borrowing constraints. These constraints imply that firms may be unable to get enough funds or must borrow at a higher cost than the risk-adjusted rate offered in a frictionless financial market. As a result, firms may save more for precautionary motives in order to (i) reduce future transaction costs when the costs of raising external funds are high (Almeida et al., 2004) or (ii) to manage potential liquidity shortfalls when external financing is not available (Han and Qiu, 2007).³ Moreover, while large export-oriented firms’ foreign earnings provide a natural hedge against financial shocks (thus reducing the need for precautionary saving)capital flow measures, such as surrender and repatriation requirements on exporters, play a role of “throwing sands in the wheels”, which could lead to excess precautionary saving.

In addition to country-level features, corporate saving behavior could also be explained by industry- and firm-level characteristics, and such characteristics can also interact with country-level features to jointly determine saving behavior. One such feature that has been extensively studied in the literature of corporate finance is external financing dependence (EFD)—a measure of a firm’s use of debt or equity issues to finance operations/investments, originally proposed by Rajan and Zingales (1998).⁴ Firms in some industries are more dependent on external financing than others for technological reasons. For examples, if an industry’s production technology requires firms to make larger initial investment and longer investment, then firms in this industry will be unlikely to generate positive operating cash flows simultaneously to finance investment projects and thus be more reliant on external funds.

Rajan and Zingales argue that in a hypothetical frictionless financial system, a firm can raise external funds equal to the optimal amount that fully reflects the technological characteristics of the industry. In contrast, in a less developed financial system, the amount of external financing raised by a firm can partly reflect the constrained access to external funds and thus is suboptimal. It follows from the precautionary and transaction cost motives that industries with high EFD⁵ are expected to be more financially constrained and tend to save more in a less developed financial system. Applying the same logic to other country-specific characteristics discussed above (e.g., capital account (KA) openness and exchange rate (ER) flexibility), one would expect that the marginal effects of these aggregate characteristics on corporate saving are also dependent on firm-specific characteristics.

This paper investigates the differential effects of country-level characteristics and policies on firm-level saving behavior, with a focus on understanding the role of industries’ export-orientation and external financing dependence in driving the differential responses of firms to aggregate factors.

The main findings are as follows. In the context of ASEAN5 countries, industries with high external financing dependence grow relatively faster in countries with more developed financial systems in the past two decades; for a given ASEAN5 country, industries that are more dependent on external financing tend to save more ceteris paribus, suggesting binding financial constraints in these countries. The impacts of KA openness and ER flexibility vary across industries with different external financing dependence and export orientation. Greater KA openness or ER depreciation reduces the average saving rate of industries with low dependence on external funds but increases the saving rate of industries with high dependence. KA opening-up or ER depreciation disproportionately reduces the saving of export-oriented industries, with an exception for exporters that are highly dependent on external funds. In addition, an improvement in the banking sector’s competitiveness or lending efficiency lowers the average corporate saving rate. Greater political stability is associated with lower corporate saving of all firms, presumably because of greater policy clarity.

The reminder of the paper is organized as follows. Section II describes the data and shows aggregate and firm-level stylized facts. Section III discusses the construction and the use of external financing dependence. Section IV presents empirical results. Section V concludes.

II. Data and Stylized Facts

This section will first elaborate on key aggregate stylized facts in ASEAN5 and then present firm-level analysis of the drivers of corporate saving from an accounting perspective.

B. Firm Level Analysis

We employ balance sheet and income statement data for a total of 3503 publicly listed firms over the period 2000–2017, drawing from the Thompson WorldScope Database.¹² 2530 firms are listed as of end-2017, with total assets accounting for 75 percent of ASEAN5 GDP (see Table A1). As the interpretation of cash and investment flows for financial corporations is different from that for non-financial corporations, we focus on the financing decisions of non-financial corporations only (see Fama and French, 2001; and DeAngelo et al., 2004). All variables are winsorized at 1 percent to remove possible effect of outliers. A drawback of the WorldScope database is that it does not include information on non-listed firms, which might have different motives for saving from listed firms. Key variables of interest are defined as follows.¹³

$$\begin{array}{c}\mathrm{Pr}ofit=GrossOperatingSurplus-Taxeson\mathrm{Pr}ofits-Interest;\\ GrossSaving=\mathrm{Pr}ofit-NetDividends;\\ NetSaving=GrossSaving-CapEx.\end{array}$$

Both gross and net saving rates of non-financial firms in ASEAN5 exhibit cyclical fluctuations during the sample period in 2000–2017 (Figure A1). The upward trend of corporate saving rates ceased in 2008 as the average firm profit was halved during the GFC, leading to a sudden dip in both gross and net corporate saving rates. After a quick recovery around 2009 and 2010, both rates began to decline since 2011 for 5 years. Although these rates picked up across the board since 2015, it is too early to judge whether the recent upswing reflects another cyclical movement or a trend. Overall, gross and net saving rates have cumulatively increased by 1.8 and 1.9 percentage points, respectively, since 2000.

Following Chen et al. (2017), firms are divided into groups i = 1,2,..., / by quartiles of size or age, and then employ a standard decomposition method to quantify the contributions of the within- and between-group components to the cumulative changes in the corporate saving rate from 2000 to 2017. Specifically, the changes in the aggregate saving rates from period t – 1 to t can be decomposed as follows:

$$\mathrm{\Delta }{s}_t=\frac{1}{2}{\mathrm{\Sigma }}_i({\omega }_{i,t}+{\omega }_{i,t-1})\mathrm{\Delta }{s}_{i,t}+\frac{1}{2}{\mathrm{\Sigma }}_i(s_{i,t}+s_{i,t-1})\mathrm{\Delta }{\omega }_{i,t},$$

where Δs_i,t = s_i,t-1 is the change in the gross (or net) saving rate of group i in period t and ω_i,t denotes the share of group i in total asset in period t. The first component in the above equation is the within-group effect; whereas the second component the between-group effect. As is shown in Table 1, the cumulative changes in the aggregate gross saving rate is entirely driven by the within-age group component. While part of the changes in the aggregate gross saving rate is due to the between-size group component, most of the changes is accounted for by changes in the within-size group component. In other words, the change in the aggregate saving rate is not mainly driven by the change in the share of old firms or large firms, relative to 2000; instead, it reflects that firms of similar age or size are behaving differently today compared to 2000, Similar trends are found in the changes in the net saving rate.

^{Table 1.}

ASEAN5: Within-between Decomposition of Changes in Saving Rate

(2000-2017, percent contribution)

Notes: The table presents results from the within-between decomposition for groups of firms i defined by quartiles of age and quartiles of size.

^{Table 1.}

ASEAN5: Within-between Decomposition of Changes in Saving Rate

(2000-2017, percent contribution)

	gross savings		net savings
	within	between	within	between
age	102.7	-2.7	117.4	-17.4
size	92.9	7.1	94.9	5.1

Notes: The table presents results from the within-between decomposition for groups of firms i defined by quartiles of age and quartiles of size.

View Table

^{Table 1.}

ASEAN5: Within-between Decomposition of Changes in Saving Rate

(2000-2017, percent contribution)

	gross savings		net savings
	within	between	within	between
age	102.7	-2.7	117.4	-17.4
size	92.9	7.1	94.9	5.1

Notes: The table presents results from the within-between decomposition for groups of firms i defined by quartiles of age and quartiles of size.

Firm-level data confirms that in case of large profits, non-financial firms in ASEAN5 tend to increase their net saving, as opposed to paying more dividends or increasing investment. The four panels of Figure A7 plot the 10-year trend in firm profit against the trends in its main components. The area of each circle corresponds to a firm’s average size over the sample period. The top panels show a strong cross-sectional relationship between trends in the gross saving rate and trends in profit relative to total assets, partly because of a weak correlation between profit and dividends. The bottom panels show that trends in investment are uncorrelated with trends in profit, leading to a meaningful positive relationship between profit and the net saving rate. These conclusions are robust if the 10-year trend is replaced with a 5-year trend.

III. External Financing Dependence

Industries have different dependence on external funds, contingent on the technological characteristics of the industry. We define the external financing dependence (EFD) at the industrial level following a two-step process developed by Rajan and Zingales (1998). First, we derive a firm’s EFD by summing the firm’s use of external finance (borrowings and equity issues, which equals total capital expenditure less cash flows from operations) over a 10-year period and then divide it by the sum of capital expenditure over the same period, i.e., (CapEx -Opt. CashFlow)/CapEx.¹⁴ Then, to summarize the EFD across all firms in an industry, we use the industry median.¹⁵

While an industry’s actual dependence on external financing may differ significantly across countries, its desired dependence on external funds is identified using the data on firms in the United States and applied to other countries. This approach is reasonable because: (i) the production functions¹⁶ of the same industry are similar across different countries—particularly, the same industry in the manufacturing sector is more likely to use similar technologies across different countries than the services sector does; and (ii) capital markets in the United States are relatively frictionless—as a result, the actual amount of external funds raised by a firm in the United States reflects the technological demand for financing, as opposed to supply constraints.

The Rajan and Zingales approach has been extensively used in the literature of corporate finance. However, 20 years have passed since the publication of Rajan and Zingales’ original paper and the EFDs of U.S. industries may have changed significantly since then for two reasons. First, incumbent firms have become more mature over the past three decades and as indicated in the previous section, mature firms save more and are thus less reliant on external funds. Second, breaking-through innovations could have fundamentally changed the production function of manufacturing and services sectors and hence the EFD of firms operating in these sectors. While it is beyond the scope of this paper to explore the impact of new technologies on firms’ reliance on external funds, we revisited the evolution of the EFD across U.S. industries/firms in order to make an informed choice of the desired EFD for firms in ASEAN5.

A few useful observations can be drawn from this exercise. First, young firms tend to depend more on external funds, as is shown by the declining median EFD of firms in the United States in Figure A8. Second, Figure A9 reveals that the distribution of EFD is generally shifting downward over time for firms listed on both NASDAQ and NYSE. Third, firms listed on NASDAQ have larger EFD than those listed on NYSE, as NASDAQ has a larger share of young and small firms than NYSE. Last, additional figures in Appendix I further show that industries’ relative rankings in different decades are relatively stable except for a few industries with larger EFD in 2010s relative to 2000s (Figure A11). Indeed, what really matters in the empirical analysis below is the EFD ranking. The magnitude of EFD is of second order. Based on these observations, the desired EFD for ASEAN5 are benchmarked, industry-by-industry, to the actual EFD of U.S. firms listed on NASDAQ in 1990s.

At the industry level, Figure A10 compares firms’ actual EFD in ASEAN5 countries (y-axis) with their desired EFD proxied by the actual EFD of their counterparts in the United States (x-axis). The size of the circle represents the average size of the associated industry in a ASEAN5 country over the sample period. While the EFD of a certain industry varies across ASEAN5 countries, there is a statistically positive relationship between the actual and desired EFD level of firms. There is a larger number of industries in ASEAN5 countries that rely more on internal funds (savings) to finance their investments than their counterparts did in the USA (i.e., below the 45-degree line in Figure A10). This fact could imply either that ASEAN5 firms are financially constrained or that they do not require as much external financing as their counterparts in USA did two decades ago. Section IV below will address this question by empirically testing the hypothesis that industries that are more dependent on external financing will have higher growth rates in countries that have more developed financial systems.

IV. Empirical Analysis

V. Conclusion

From a global perspective, it has been well-documented that the non-financial corporate sector has shifted from a net borrower to a net saver over the past two decades. But the literature on corporate saving in emerging markets is relatively sparse and incomplete. ASEAN5 is a vibrant region that has been heavily integrated in the GVC and attracted substantial international capital flows. Corporate saving rates in ASEAN5 show cyclical fluctuations, as opposed to the upward trend in advanced economies. This can be partly explained by the unique features of ASEAN5 economies.

Using an extensive firm-level data set with comprehensive information on balance sheets and income statements for ASEAN5 countries, this paper studies the differential effects of macro-financial and structural factors on corporate saving behavior. It confirms that non-financial corporations in ASEAN5 may be subject to binding financial constraints: (i) in a given period, industries with high external financing dependence grow relatively faster in countries with more developed financial systems; (ii) in a given country, industries that are more dependent on external financing, ceteris paribus, tend to save more. The impacts of KA openness and ER flexibility vary across industries with different external financing dependence and export orientation. Greater KA openness or ER depreciation reduces the average saving rate of industries with low dependence on external funds but increases the saving rate of industries with high dependence. KA opening-up or ER depreciation disproportionately reduces the saving rate of export-oriented industries, with an exception for exporters that are highly dependent on external funds. An improvement in the banking sector competition or banks’ lending efficiency lowers the corporate saving rate on average. Greater political stability (lower policy uncertainty) is associated with lower net saving rate of all firms.

While this paper investigates the aggregate and micro drivers of actual corporate saving rates in ASEAN5, it remains a question whether the actual corporate saving rate exceeds the desired saving rate and to what extent the gap between the two saving rates contributes to a country’s overall external imbalance. To address this question, a first challenge is how to conceptually define and empirically estimate the desired level of corporate saving. While this is beyond the scope of this paper, the above analysis sheds some light on a possible way forward. First of all, the desired saving rate of a firm should be a function of its external financing dependence, which is in turn determined by the production technology of its industry. Of course, one should factor in firm maturity as research show that young firms are more dependent on external funds than mature ones. In addition to the industry-level EFD, some firm-level characteristics may be also relevant, such as the export-orientation rate and firm ownership. As is shown in the paper, these firm- and industry-level fundamentals always interact with aggregate factors. Therefore, one would also need to define the desirable levels of relevant macro and financial factors/policies, such as the desirable levels of financial development, KA openness, ER flexibility etc. Further research along these lines would be needed to deepen the understanding around external imbalances, given the importance of the self-financing behavior of credit-constrained firms in rapidly growing emerging markets.