Cash holdings and their implication on product market performance.

Cash holdings and their implication on product market

performance.

Student Number: s3816834

Name: Giacomo Reghelin

Study Program: MSc IFM

Supervisor: Dr. H. Gonenc

Co-assessor: Dr. E. Karmaziene

Field Key Words: Cash holdings, product market performance, global diversification, industrial diversification, country’s investor protection.

Abstract

Table of contents

Abstract ... 1

1. Introduction ... 3

2. Literature review and Hypothesis development... 5

2.1. Cash holdings and product market performance ... 5

2.2. Diversification and the effect of cash holdings on sales growth and market share growth ... 8

2.3. Country’s strength of investor protection ... 11

3. Data and Methodology ... 14

3.1. Data and sample selection ... 14

3.2. Empirical models ... 14

3.2.1. Cash holdings and market performance ... 14

3.2.2. Global and Industry Diversification ... 18

3.2.3. Country-level investor protection ... 19

3.3. Descriptive statistics ... 19

4. Results ... 23

4.1. Cash holdings and market performance ... 23

4.2. Global and industrial diversification ... 26

1. Introduction

Several authors have reported how in the recent decades cash holdings are increasing in companies and tried to understand the reasons behind this trend. Pinkowitz, Stulz, and Williamson (2016) report that, in their sample of US companies, the cash-to-asset ratio increased from 16% to 21% from 1998 to 2011. Nowadays, this concern is still a sensitive issue. The Financial Times reports in February 2019 that “venture capital investors are warning their start-ups to hold more cash as worries about the global economy and stock market volatility threaten to trickle down into private tech financings”. These figures inevitably drive practitioners to investigate the reasons behind cash holdings. Chief among these motives is the precautionary one. According to the precautionary motive, companies hold more cash in order to be more ready to exploit future market growth possibilities and to prevent future negative shocks in fund raising. Although several studies confirm the validity of this theory (see, e.g., Bates, Kahle, and Stulz, 2009; He and Wintoki, 2016), they mostly focus on the determinants of cash holdings, and pay little attention to the effect that cash policy has on firm’s day-to-day operations. Fresard (2010) starts from this evidence and analyzes the impact that liquidity has on the product market behavior of US companies, finding that holding more cash than competitors has a direct positive effect on future market share growth.

is important to investigate how this relationship is affected by both firm- and country-level characteristics. Previous studies argued that the company levels of global and industrial diversification play an important role in cash policy. Tong (2011) argues that diversification leads to inefficient allocation of cash, while Bakke and Gu (2017) suggest that higher levels of diversification require the company to face higher costs. As a consequence, diversified companies lose part of their capacity to use cash reserves to foster sales growth. At the same time, diversification endows companies with strategic advantages such as synergies, know-how, flexibility and new growth opportunities (Gu, 2017; Jandik and Makhija, 2005), which could increase the benefits of cash reserves and further gain market share. Moreover, the benefits of cash in terms of market performance could change based on country’s conditions. Stronger investor protection leads companies to better allocate their resources, making cash reserves a more valuable instrument to boost sales growth (Huang, Elkinawy, and Jain, 2013). However, better access to finance reduces the strategic advantage of cash in terms of market share: not only cash-rich firms can capture growth opportunities but also new entrants which can easily raise funding (Malamud and Zucchi, 2019). Thus, after investigating the effect of cash holdings on market performance, I consider how this could be affected by both firm- and country-level variables. In particular, I consider two dimensions of corporate diversification: global and industrial diversification. I analyze how being either internationally or industrially diversified, as well as their interaction, moderates the main relationship. Finally, I test whether the positive effect of cash is stronger or weaker in countries with different levels of investor protection.

reduces the ability of companies to use their cash holdings to increase sales volume. However, when considered jointly, global and industrial diversification weakens each other’s negative effect on the relationship between cash holdings and sales growth. In relative-to-competitor terms, being more diversified than rivals leads to strategic advantages that enhance companies to better use their cash position to gain market share. The two diversification dimensions, when considered together, strengthen each other’s positive effect. Finally, results do not strongly support the idea that the strength of country’s investor protection moderates the main relationship.

This thesis contributes to the existing literature on cash holdings by testing the real implication of holding liquidity on market performance, both in absolute and relative-to-competitor terms. Fresard (2010) analyzes this relationship in a domestic sample of US firms and only in relative-to-rival terms, while I extend his findings to an international sample and implement another measure of market performance: sales growth. Moreover, this thesis contributes to the current literature on the effect of industrial and global diversification on corporate choices. To the best of my knowledge, no prior study has analyzed how these two dimensions of diversification, both singularly and together, moderate the effect of cash on market performance. Finally, it also extends the literature on the relationship between shareholder protection and cash policy.

The reminder of this thesis is organized as follows: Section 2 reviews the existing literature on cash holdings, market performance, diversification and investor protection, and also present this thesis’s hypotheses. In Section 3, I discuss the data, empirical methods and variables. Section 4 contains the results and conclusions are presented in Section 5.

2. Literature review and Hypothesis development 2.1. Cash holdings and product market performance

Keynes (1936), is proven to have reliable explanatory power for cash policy. The precautionary theory, according to Bates, Kahle, and Stulz (2009), asserts that companies hold more cash in order to cope with future adverse shocks that may increase the cost of funding. Their study (in line with the previous one of Han and Qiu, 2007) confirms that the precautionary motive is a relevant tool to explain the increase in cash holdings since firms with higher cash levels are also found to be characterized by riskier cash flows: the precautionary importance of cash increases when there is higher uncertainty about future earnings. Moreover, the precautionary motive implies that firms hold liquidity for being ready to exploit future growth opportunities (Fernandes and Gonenc, 2016; Harris and Raviv, 2017) thus, cash reserves are a tool to ensure business growth and development (La Rocca and Cambrea, 2019). In line with this concept, He and Wintoki (2016) point out that R&D investments explain a significant part of the increase in US firms’ cash holdings. Similarly, Bates, Chang, and Chi (2018) argue that, in particular during the 1990s, the increase in value of cash is driven by investment opportunities and product market competition, suggesting that there are benefits to liquidity associated with growth opportunities and market performance. Although prior studies show that the precautionary motive plays a key role in explaining higher cash holdings, the main question would be: if companies hold more cash in order to be ready to exploit future market opportunities, is it true that they are actually able to do so?

with this, Chi and Su (2016) suggest that more liquid firms can induce financially weaker rivals to underinvest, thus ensuring gains in their market share. They conclude that “cash becomes more valuable because it provides unconditional liquidity to readily capture investment opportunities as they emerge” (p. 706). Moreover, Haushalter, Klasa, and Maxwell (2007) suggest that larger cash reserves serve as a source of competitive advantage since high liquidity allows firms to increase investment when the average industry-level is decreasing. They argue that cash holdings enable to make planned investment, with the added advantage of decreasing predation risk and preventing competitors from gaining strategic advantages. Overall, this proves that liquid firms “try to gain market share by increasing investment when changes in industry conditions force rivals to reduce investment” (p. 818). Lyandres and Palazzo (2016) argue that liquidity is of paramount importance when it comes to finance innovation, which is one of the main drivers of growth. In particular, they find that firms with higher cash holdings are more likely to invest in innovation resulting in product market advantages and consequent market share growth. Finally, the literature proposes further indirect benefits of cash on market performance. Chang et al. (2019) argue that cash holdings serve as a commitment device to assure credibility and earn trust from stakeholders which are important sources of competitive advantage. He (2018) shows that large cash reserves enable firms to “gain labor market shares at the expense of rivals, leading to superior product market performance [proxied by growth in sales and growth in market share]” (p. 229).

Garfinkel, and Yu (2017) run a series of regressions where they consider different variables as proxy of product market output, such as sales growth and market share growth (the same used in the above-mentioned studies). In all their specifications, the effect of cash is positive and significant, proving that cash reserves directly improve firm’s product market position.

In conclusion, these sets of studies prove that cash (both directly and indirectly) improve the product market position of a company. However, to the best of my knowledge, these results are confined to US firms. My intention is to expand the sample to a worldwide framework and test whether cash holdings have a positive effect on product market performance both in absolute (sales growth) and relative-to-competitor (market share growth) terms.

H1: The impact of cash holdings on product market performance will be positive.

2.2. Diversification and the effect of cash holdings on sales growth and market share growth Literature has widely covered the topic of how diversification impacts on cash holdings and firm performance. However, little has be done to study its role in the relationship between cash reserves and product market performance. This thesis focuses on the impact that both global diversification and industrial diversification, as well as the interaction between the two, have on the relationship between cash and market performance. In particular, having identified two measures of market performance (sales growth and market share growth), I argue that diversification has a different moderating effect depending on the measure of market performance used.

are more easily used by managers in a discretionary way for private benefits. Thus, the power of cash to boost sales growth is more likely to be weaker in diversified firms. Finally, in contrast to the efficient internal capital market theory, Rajan, Servaes, and Zingales (2000) propose that a diversification strategy leads to an “imperfect external capital market” (p. 36). In particular, they argue that the management of divisions will use the available resources for the sole purpose of ensuring that the headquarter will not reallocate them into other divisions. Thus, each segment will use its liquid resources not to pursue the best strategy for the company as a whole, but to ensure minimum and safer earnings. Consequently, the operating benefits of cash will be weaker in diversified firms. Taken together, the above-mentioned studies suggest that diversified firms will lower their cash reserves and use liquidity for reasons other than sales growth.

H2: Corporate diversification will weaken the positive effect of cash holdings on sales growth.

(2017) argue that a strategy of industrial diversification where a company homogeneously distributes its activities among business segments and is equally committed to them, allows the company to achieve strategic advantages such as synergies, economies of scope and market power. This, again, supports the idea that a higher degree of diversification than competitors endows firms with instruments to increase the benefits of cash reserves in terms of market share.

Together, the above arguments lead to the following hypothesis:

H3: Corporate diversification will strengthen the positive impact of cash holdings on market share growth.

Since companies that operate internationally face also different product markets, several multinational firms implement an industrial diversification strategy too (Chang and Wang, 2007). Prior literature argues the importance that the joint effect of the two diversification strategies has in terms of cash policy (Fernandes and Gonenc, 2016) and market performance (Geringer, Tallman, and Olsen, 2000). This suggests that the combined effect of global and product diversification could be interesting for the relationship between cash holdings and market performance. Regardless of the effect that diversification has on the relationship between cash holdings and market performance (positive or negative) and regardless of the measure of market performance implemented (sales growth or market share growth), it can be argued that, taken together, the two dimensions of diversification either strengthen or weaken each other’s effect.

assumption, Fernandes and Gonenc (2016) find that the global and industrial diversification substitute each other’s negative effect in terms of cash policy.

When market performance is defined in relative-to-competitor terms, H3 suggests that diversification strengthens the positive effect that cash has on market share growth. For the same arguments, it could be that the two dimensions of diversification jointly reinforce each other’s positive effect. Being true that diversification develops knowledge and inputs which enable companies to use their cash holdings to gain market share, increasing both the product and geographical diversification should result in an even stronger positive effect. Indeed, Chang and Wang (2007) suggest that when multi-product companies expand in international markets, there are greater opportunities to achieve synergies and exploit competitive advantages. However, they also argue that “implementing both dimensions of diversification may be detrimental to firm performance” (p. 63). This is because a more complex structure leads to higher integration costs which will shrink cash reserves and weaken their strategic advantages in terms of market share growth.

Taken together, the above argumentations present two possible alternative scenarios:

H4a: Global and industrial diversification together will weaken each other’s effect on the relationship between cash holdings and product market performance.

H4b: Global and industrial diversification together will strengthen each other’s effect on the relationship between cash holdings and product market performance.

Where product market performance is first defined as sales growth, and then represented by market share growth.

2.3. Country’s strength of investor protection

(McLean and Zhao, 2018). Moreover, it is also a significant determinant of a company’s growth opportunities (Beck, Demirgüç-Kunt, and Maksimovic, 2006). Thus, it seems reasonable to investigate how the relationship between cash holdings and market performance changes with different levels of country’s shareholder protection.

H5: The strength of investor protection of the country in which the firm operates will strengthen the positive effect of cash holdings on sales growth.

protection is stronger, firms hold lower cash reserves and are less capable of using them to foster their market share.

H6: The strength of investor protection of the country in which the firm operates will weaken the positive effect of cash holdings on market share growth.

3. Data and Methodology 3.1. Data and sample selection

I gathered the initial sample from Asset4, available at Thomson Reuters Datastream, for the period 2002-2017. Following Bates, Chang, and Chi (2018), I exclude financial firms (SIC codes 6000-6999) since their liquidity level is affected by reserve requirements, and utilities (SIC codes 4900-4999) which are subject to regulatory oversight. Finally, I exclude all firm-years with missing observations for total sales, cash holdings and total assets. The final sample consists of 40,746 observations, relative to 4,693 firms operating in 44 countries.

3.2. Empirical models

3.2.1. Cash holdings and market performance

In order to test the first hypothesis of this thesis, ordinary least squares (OLS) regressions are estimated. I consider the following regression model:

MKT PERFORMANCE𝑖,𝑡 = 𝛽0+ 𝛽1CASH HOLDINGS𝑖,𝑡−1+ 𝛽2MKT PERFORMANCE𝑖,𝑡−1+

𝛽₃SIZE_{𝑖,𝑡−1}+ 𝛽₄TOBIN’S Q_{𝑖,𝑡−1}+ 𝛽₅FIXED ASSETS GROWTH_{𝑖,𝑡−1}+ 𝛽₆CAPEX _{𝑖,𝑡−1}+ 𝛽₇R&D_{𝑖,𝑡−1}+

𝛽₈SELLING EXPENSES_{𝑖,𝑡−1}+ 𝛽₉LEVERAGE _{𝑖,𝑡−1}+ 𝛽₁₀N. GEO REGIONS_{𝑖,𝑡−1}+

𝛽₁₁N. SEGMENTS_{𝑖,𝑡−1}+ 𝛽₁₂ANTI˗SELF˗DEALING_𝑘+ 𝜏_𝑡+ 𝜂_𝑗+ 𝜖_𝑖 (1)

Where i is a subscription for each firm, t for each year, k for each country and j for each industry. 𝜏𝑡 is a set of yearly dummies and 𝜂𝑗 of industry dummies. Within-firm clustered standard errors

In line with the study of Billett, Garfinkel, and Yu (2017), I measure the product market performance (MKT PERFORMANCE) of a company in two ways: with its sales growth and with its market share growth. SALES GROWTH is computed as the percentage change in sales between one year and the previous one (Equation 2a). MKT SHARE GROWTH, (which is the same dependent variable used by Fresard, 2010) measures the firm’s product market performance relative to its competitors. In particular, this variable is sales growth minus the country-industry-year average sales growth, where industry is classified using the two-digit SIC code (Equation 2b). This variable represents a “practical measure of performance that incorporates information from the combined effects of pricing and other market strategies” and can be referred as market share growth (Campello, 2003, p. 366).

SALES GROWTH𝑖,𝑡 =SALES_SALES𝑖,𝑡− SALES𝑖,𝑡−1

𝑖,𝑡−1 (2a)

MKT SHARE GROWTH𝑖,𝑗,𝑡 = SALES GROWTH𝑖,𝑡− SALES GROWTH𝑘,𝑗,𝑡 (2b)

Where i is a subscription for each firm, t for each year, k for each country and j for each industry.

zCASH_{𝑖,𝑗,𝑡} =CASH˗TO˗ASSET𝑖,𝑗,𝑡− µ(CASH˗TO˗ASSET𝑖,𝑗,𝑡)

𝜎(CASH˗TO˗ASSET𝑖,𝑗,𝑡) (3) Where µ and 𝜎 indicate the country-industry-year mean and standard deviation respectively.

which is detrimental for company’s growth (Zahra, Ucbasaran, and Newey, 2009; Geringer, Tallman, and Olsen, 2000; Chang and Wang, 2007). Finally, I also control for the country-level investor protection, proxied by ANTI-SELF-DEALING (Djankov et al., 2008). Stronger shareholder rights are thought to increase growth opportunities (Beck, Demirgüç-Kunt, and Maksimovic, 2006) and prevent management from using cash for personal interests, thus boosting market performance. However, this factor could also encourage new entrants and disruptive innovations which jeopardize incumbents’ market performance (Malamud and Zucchi, 2019). When market share growth is used as dependent variable, the aim of the model is to identify whether higher relative-to-competitor cash holdings foster product market performance. Thus, in order to better capture the relative-to-rival aspect, all control variables are adjusted for their year-country-industry average value. All variables used in this thesis are defined in table 10, Appendix A.

fulfills the requirements for a relevant instrument: being correlated with the variable of interest and exogenous.

3.2.2. Global and Industry Diversification

To test hypotheses 2 and 3, I consider how diversification variables moderate the relationship between cash holdings and market performance. In particular, I implement the following model:

MKT PERFORMANCE_𝑖,𝑡 = 𝛽₀+ 𝛽₁CASH HOLDINGS_{𝑖,𝑡−1}+ 𝛽₂DIVERSIFICATION_{𝑖,𝑡−1}+

𝛽₃CASH HOLDINGS_{𝑖,𝑡−1}∗ DIVERSIFICATION_{𝑖,𝑡−1}+ 𝛽₄MKT PERFORMANCE_{𝑖,𝑡−1}+ 𝛽₅SIZE_{𝑖,𝑡−1}+ 𝛽₆TOBIN’S Q_{𝑖,𝑡−1}+ 𝛽₇FIXED ASSETS GROWTH_{𝑖,𝑡−1}+ 𝛽₈CAPEX _{𝑖,𝑡−1}+ 𝛽₉R&D_{𝑖,𝑡−1}+

𝛽₁₀SELLING EXPENSES_{𝑖,𝑡−1}+ 𝛽₁₁LEVERAGE _{𝑖,𝑡−1}+ 𝛽₁₂ANTI˗SELF˗DEALING_𝑘+ 𝜏_𝑡+ 𝜂_𝑗+ 𝜖_𝑖 (4)

growth. Conversely, when 𝛽₃ is positive and the dependent variable is market share growth, H3 will be supported. Then, in order to test H4a and H4b, I also run a specification in which both dimensions of diversification are included and are interacted together with cash holdings to test whether they jointly affect the relationship between cash and product market performance.

3.2.3. Country-level investor protection

Finally, to understand whether a country-level variable (ANTI-SELF-DEALING) affects the relationship between cash holding and market share gains, I implement the following model:

MKT PERFORMANCE_𝑖,𝑡 = 𝛽₀+ 𝛽₁CASH HOLDINGS_{𝑖,𝑡−1}+ 𝛽₂ANTI˗SELF˗DEALING_𝑘+

𝛽₃CASH HOLDINGS_{𝑖,𝑡−1}∗ ANTI˗SELF˗DEALING_𝑘+ 𝛽₄MKT PERFORMANCE_{𝑖,𝑡−1}+ 𝛽₅SIZE_{𝑖,𝑡−1}+ 𝛽₆TOBIN’S Q_{𝑖,𝑡−1}+ 𝛽₇FIXED ASSETS GROWTH_{𝑖,𝑡−1}+ 𝛽₈CAPEX _{𝑖,𝑡−1}+ 𝛽₉R&D_{𝑖,𝑡−1}+

𝛽₁₀SELLING EXPENSES_{𝑖,𝑡−1}+ 𝛽₁₁LEVERAGE _{𝑖,𝑡−1}+ 𝛽₁₂N. GEO REGIONS_{𝑖,𝑡−1}+

𝛽₁₃N. SEGMENTS_{𝑖,𝑡−1}+ 𝜏_𝑡+ 𝜂_𝑗+ 𝜖_𝑖 (5)

With market performance represented by either sales growth or market share growth. The country-level variable is the Anti-Self-Dealing Index, developed by Djankov et al. (2008), which is meant to capture the strength of protection of small investors. In Equation 5, the variable of interest is the coefficient of the interaction term (𝛽₃). When sales growth is used as dependent variable, I expect the interaction term to be positive (H5), while, when market share growth is used, H6 suggests a negative coefficient.

3.3. Descriptive statistics

Table 2 reports the summary statistics by country. The table pinpoints that the sample is dominated by US companies, making up for almost 50% of the observations. The country characterized by the highest value of ANTI-SELF-DEALING index is Singapore, while Mexico, with a value of 0.178, appears to be the country with weakest investor protection.

Finally, Table 3 shows the correlation coefficients among variables used in the empirical analyses. In both panels, the dependent variables (SALES GROWTH in Panel A and MKT SHARE GROWTH in Panel B) and the cash holdings variables (CASH-TO-ASSET and zCASH) are positively correlated, suggesting that, in general, higher liquidity is associated with higher market performance. The correlation coefficient is significant at 1% level.

Table 1. Descriptive statistics by variable Panel A

Variable Obs. Median Mean Std. Dev. Min. Max.

SALES GROWTH 40,746 0.073 0.132 0.392 -0.584 3.399 CASH-TO-ASSET 40,746 0.114 0.171 0.173 0.001 0.903

SIZE 40,746 14.630 14.622 1.670 9.354 18.493

TOBIN’S Q 40,746 1.569 2.048 1.460 0.642 9.558

FIXED ASSET GROWTH 40,746 0.044 0.131 0.449 -0.565 3.914

CAPEX 40,746 0.037 0.054 0.056 0.000 0.344 SELLING EXPENSES 40,746 0.161 0.218 0.205 0.006 1.174 LEVERAGE 40,746 0.153 0.183 0.175 0.000 0.829 R&D 40,746 0.001 0.030 0.063 0.000 0.420 N. GEO REGIONS 40,746 2.000 2.592 1.569 1.000 10.000 N. SEGMENTS 40,746 1.000 1.614 0.930 1.000 9.000 ANTI-SELF-DEALING 40,746 0.651 0.636 0.160 0.178 1.000 ASSET TANGIBILITY 40,538 0.331 0.316 0.129 0.013 0.545 Panel B

Variable Obs. Median Mean Std. Dev. Min. Max.

MKT SHARE GROWTH 40,746 -0.047 -0.247 1.079 -7.614 2.090

zCASH 40,746 -0.287 -0.033 0.883 -1.370 2.714

RC_SIZE 40,746 0.079 0.144 1.378 -3.763 3.599

RC_TOBIN’S Q 40,746 -0.201 -0.124 1.352 -4.341 6.123 RC_FIXED ASSET GROWTH 40,746 -0.063 -0.324 1.591 -12.842 2.506

Table 2. Descriptive statistics by country COUNTRY N. SALES GROWTH CASH-TO-ASSET N. GEO REGIONS N. SEGMEN TS ANTI- SELF-DEALING CREDITO RS RIGHTS Argentina 25 -0.010 0.105 1.320 2.200 0.444 1.000 Austria 15 0.161 0.097 3.000 1.733 0.209 3.000 Australia 1,439 0.258 0.152 1.965 1.568 0.790 3.000 Belgium 126 0.088 0.168 3.143 1.429 0.540 2.000 Brazil 345 0.092 0.165 1.959 1.548 0.291 1.000 Canada 2,353 0.208 0.105 2.298 1.322 0.651 1.000 Switzerland 490 0.094 0.205 4.094 1.631 0.267 1.000 Chile 47 0.018 0.081 2.894 2.170 0.625 2.000 China 1,424 0.250 0.188 1.598 2.105 0.778 2.000 Czech Republic 19 0.108 0.085 4.211 1.053 0.340 3.000 Germany 934 0.078 0.140 3.769 1.796 0.279 3.000 Denmark 173 0.108 0.186 3.751 1.428 0.466 3.000 Egypt 11 -0.070 0.054 1.091 1.000 0.491 2.000 Spain 93 0.092 0.142 3.398 1.462 0.370 2.000 Finland 103 0.035 0.125 5.466 1.728 0.460 1.000 France 577 0.065 0.125 4.428 1.872 0.382 0.000 United Kingdom 2,589 0.095 0.117 2.981 1.559 0.927 4.000 Greece 58 0.054 0.113 2.362 2.500 0.225 1.000 Hong Kong 1,086 0.182 0.215 2.291 2.152 0.964 4.000 Indonesia 244 0.099 0.158 1.475 1.971 0.683 2.000 Ireland 36 0.031 0.129 3.000 1.444 0.787 1.000 Israel 89 0.101 0.179 2.831 1.124 0.714 3.000 India 70 0.156 0.227 3.286 1.186 0.549 2.000 Italy 215 0.068 0.115 3.781 1.981 0.385 2.000 Japan 3,877 0.054 0.171 2.959 2.130 0.483 2.000 Korea (South) 542 0.084 0.131 2.893 2.279 0.461 3.000 Luxembourg 19 -0.004 0.080 5.579 1.105 0.249 . Mexico 147 0.069 0.112 2.592 1.585 0.178 0.000 Malaysia 195 0.083 0.139 2.385 2.805 0.948 3.000 Netherlands 209 0.066 0.133 4.349 1.464 0.209 3.000 Norway 123 0.064 0.111 4.106 1.545 0.435 2.000 New Zealand 52 0.127 0.118 2.692 1.423 0.950 4.000 Peru 70 0.032 0.091 2.429 1.643 0.408 0.000 Philippines 36 0.121 0.150 1.611 2.111 0.237 1.000 Poland 53 0.262 0.134 2.302 1.528 0.300 1.000 Portugal 27 0.066 0.127 1.889 1.407 0.486 1.000 Russian Federation 187 0.134 0.105 2.658 1.663 0.476 2.000 Sweden 484 0.103 0.091 4.279 1.748 0.340 1.000 Singapore 205 0.140 0.172 2.995 2.298 1.000 3.000 Thailand 133 0.092 0.155 2.113 1.511 0.849 2.000 Turkey 91 0.059 0.191 1.835 1.176 0.426 2.000 Taiwan 1,058 0.089 0.198 2.809 1.694 0.560 2.000 USA 20,203 0.140 0.192 2.393 1.429 0.651 1.000 South Africa 474 0.075 0.113 2.304 1.916 0.814 3.000 Total 40,746 0.132 0.171 2.592 1.614 0.636 1.655

Table 3. Correlation table Panel A Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (1) SALES GROWTH 1.000 (2) CASH-TO-ASSET 0.134* 1.000 (3) SIZE -0.133* -0.337* 1.000 (4) TOBIN’S Q 0.188* 0.423* -0.336* 1.000

(5) FIXED ASSET GROWTH 0.365* 0.069* -0.081* 0.136* 1.000

(6) CAPEX 0.094* -0.181* -0.025* -0.014* 0.171* 1.000 (7) SELLING EXPENSES 0.015* 0.278* -0.372* 0.375* -0.026* -0.124* 1.000 (8) LEVERAGE -0.045* -0.306* 0.221* -0.143* -0.031* 0.071* -0.167* 1.000 (9) R&D 0.107* 0.542* -0.288* 0.343* 0.036* -0.157* 0.429* -0.154* 1.000 (10) N. GEO REGIONS -0.105* -0.029* 0.273* -0.097* -0.083* -0.133* -0.066* -0.038* 0.065* 1.000 (11) N. SEGMENTS -0.067* -0.147* 0.288* -0.152* -0.051* -0.098* -0.150* 0.015* -0.148* 0.081* 1.000 (12) ANTI-SELF-DEALING 0.062* 0.013* -0.188* 0.077* 0.060* 0.042* 0.013 -0.006 -0.053* -0.193* -0.030* 1.000 (13) ASSET TANGIBILITY -0.069* -0.514* 0.097* -0.249* -0.044* 0.425* -0.170* 0.020* -0.351* -0.017* 0.064* -0.011 1.000 Panel B Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (1) MKT SHARE GROWTH 1.000 (2) zCASH 0.063* 1.000 (3) RC_SIZE -0.076* -0.259* 1.000 (4) RC_TOBIN’S Q 0.085* 0.300* -0.264* 1.000

(5) RC_FIXED ASSET GROWTH 0.423* 0.041* -0.063* 0.064* 1.000

4. Results

4.1. Cash holdings and market performance Table 4. Cash holdings and sales growth Dependent Variable: SALES

GROWTH

(1) (2) (3) (4)

OLS OLS OLS OLS

CASH˗TO˗ASSET_𝑡−1 0.130*** 0.134*** 0.138*** 0.135*** (0.022) (0.021) (0.021) (0.021) SALES GROWTH_𝑡−1 0.104*** 0.107*** 0.109*** 0.107*** (0.013) (0.013) (0.013) (0.013) SIZE_𝑡−1 -0.028*** -0.024*** -0.027*** -0.025*** (0.002) (0.002) (0.002) (0.002) TOBIN′_{S Q} 𝑡−1 0.032*** 0.031*** 0.032*** 0.031*** (0.003) (0.003) (0.003) (0.003) FIXED ASSET GROWTH𝑡−1 0.126*** 0.127*** 0.127*** 0.127***

(0.010) (0.010) (0.010) (0.010) CAPEX_𝑡−1 0.079 0.092 0.111* 0.096* (0.058) (0.058) (0.058) (0.058) SELLING EXPENSES_𝑡−1 -0.165*** -0.168*** -0.171*** -0.167*** (0.014) (0.014) (0.014) (0.014) LEVERAGE_𝑡−1 0.053*** 0.031** 0.034** 0.032** (0.015) (0.014) (0.014) (0.014) R&D_𝑡−1 0.376*** 0.345*** 0.341*** 0.346*** (0.071) (0.070) (0.070) (0.070) N. GEO REGIONS_𝑡−1 -0.009*** -0.009*** (0.001) (0.001) N. SEGMENTS𝑡−1 0.004** 0.004** (0.002) (0.002) ANTI˗SELF˗DEALING𝑘 0.016 0.022** 0.015 (0.010) (0.010) (0.010) Constant 0.382*** 0.419*** 0.418*** 0.414*** (0.057) (0.033) (0.032) (0.033) Observations 40,746 40,746 40,746 40,746

Year fixed effects Yes Yes Yes Yes

Country fixed effects Yes No No No

Industry fixed effects Yes Yes Yes Yes

R-squared 0.169 0.166 0.165 0.166

This table shows the impact of the level of cash holdings on firms’ product market performance, which is represented by sales growth. The dependent variable (SALES GROWTH) is calculated as percentage change in sales from one year to the next one. The variable of interest is CASH-TO-ASSET, which corresponds to cash and short-term investments divided by book value of total asset. Standard error in parenthesis are clustered at the firm-level. The sample period is 2002-2017. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

prediction that liquid firms have a competitive advantage when it comes to product market performance. In particular, the coefficients of CASH-TO-ASSET in Table 4 are positive (between 0.130 and 0.138) and significant at 1% level. When it comes to control variables, the results are generally in line with expectations: SIZE enters negatively, while TOBIN’S Q and FIXED ASSET GROWTH have a positive coefficient. This supports the prediction that firms at a younger stage of their business life are expected to have higher sales growth. It also appears that companies engaging in more aggressive spending strategies have an advantage in terms of product market performance: R&D and CAPEX have positive coefficients. However, against predictions, SELLING EXPENSES enters the model negatively. In contrast with the results of Billett, Garfinkel, and Yu (2017), the coefficient of LEVERAGE is positive, suggesting that a higher level of indebtedness boosts sales growth. In Columns 2 to 4, company’s diversification variables (N. GEO REGIONS and N. SEGMENTS), as well as the strength of country’s investor protection (ANTI-SELF-DEALING) are introduced: the coefficient of cash holdings remains positive and significant. Results do not change when CREDITOR RIGHTS (defined in Table 10 in Appendix A) is used as proxy of shareholder protection. In an unreported table, I also run weighted least squares (WLS) regressions using the same models in Table 4, where the weights are the inverse of the number of observations in a country. Doing so, each country receives equal weight in the estimations. Again, the coefficient of CASH-TO-ASSET is positive and significant (between 0.142 and 0.153).

Table 5. Cash holdings and market share growth Dependent Variable: MKT

SHARE GROWTH

(1) (2) (3) (4)

OLS OLS OLS OLS

zCASH_𝑡−1 0.017*** 0.017*** 0.017*** 0.018*** (0.006) (0.006) (0.006) (0.006) MKT SHARE GROWTH_𝑡−1 0.057*** 0.074*** 0.074*** 0.074*** (0.008) (0.009) (0.009) (0.009) RC_SIZE_𝑡−1 -0.037*** -0.036*** -0.039*** -0.037*** (0.004) (0.004) (0.004) (0.005) RC_TOBIN′_{S Q} 𝑡−1 0.026*** 0.026*** 0.026*** 0.026*** (0.005) (0.005) (0.005) (0.005) RC_FIXED ASSET GROWTH_𝑡−1 0.064*** 0.065*** 0.065*** 0.065***

(0.005) (0.005) (0.005) (0.005) RC_CAPEX𝑡−1 0.426** 0.410** 0.425** 0.420** (0.166) (0.171) (0.171) (0.172) RC_SELLING EXPENSES𝑡−1 -0.169*** -0.164*** -0.165*** -0.164*** (0.038) (0.037) (0.037) (0.037) RC_LEVERAGE_𝑡−1 0.037 0.043 0.045 0.043 (0.036) (0.037) (0.037) (0.037) RC_R&D_𝑡−1 1.051*** 1.176*** 1.178*** 1.177*** (0.167) (0.169) (0.169) (0.169) RC_N. GEO REGIONS𝑡−1 -0.006 -0.006 (0.004) (0.004) RC_N. SEGMENTS_𝑡−1 0.010* 0.010* (0.006) (0.006) ANTI˗SELF˗DEALING𝑘 -0.130*** -0.130*** -0.130*** (0.032) (0.032) (0.032) Constant 0.138** 0.256*** 0.255*** 0.256*** (0.070) (0.043) (0.042) (0.043) Observations 40,746 40,746 40,746 40,746

Year fixed effects Yes Yes Yes Yes

Country fixed effects Yes No No No

Industry fixed effects Yes Yes Yes Yes

R-squared 0.184 0.170 0.170 0.170

This table shows the impact of the level of cash holdings on firms’ product market performance, where product market performance is represented by market share growth. The dependent variable (MKT SHARE GROWTH) is calculated as sales growth minus rivals (country-industry-year) sales growth. The variable of interest is zCASH, which corresponds to the difference between company’s cash-to-asset and its year average, divided by its country-industry-year standard deviation. Standard error in parenthesis are clustered at the firm-level. The sample period is 2002-2017. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

observations may affect the reliability of cash deviation, therefore, in an unreported table, only country-industry-years with at least 30 companies are considered. The coefficients of the cash holdings variables are significant and higher in value (between 3.4% and 3.8%), however, the number of total observations is considerably reduced to 18,212.

Besides the previous analyses, H1 is tested also with two-stage least squares (2SLS) regressions to tackle the reverse causality concerns in the relationship between cash holdings and market performance. Appendix B (Tables 11 and 12) reports regression tables where the CASH-TO-ASSET and zCASH are instrumented by their lagged values and by asset tangibility (Fresard, 2010). The results of the 2SLS regressions show that the coefficient of cash holdings is always positive and significant, thus supporting the previous findings and H1.

4.2. Global and industrial diversification

This section explores the implications in hypothesis 2 to 4. In particular, I implement the model in Equation 4 to analyze the impact that diversification has on the relationship between cash holdings and product market performance.

suggesting that diversification weakens the positive effect of cash holdings on sales growth. The difference between the coefficients of cash holdings for the two subsamples is significant at 1% level. In addition, column 3 considers the joint effect of both geographical and industrial diversification. The positive and significant coefficient of the three-way interaction term suggests that the two dimensions of diversification do not strengthen but weaken each other’s effect. Indeed, although both diversification dimensions alone weaken the positive effect of cash holdings on sales growth, a strategy that implements both of them will strengthen more the main relationship than one characterized by only global or industrial diversification. This idea finds further support in the comparison analysis between columns 4 and 5. A higher level of industrial diversification has a stronger negative impact on the main relationship for those companies that are not globally diversified, while, for international companies, an increase in industrial diversification does not affect the relationship between cash holdings and sales growth. The difference of the coefficients of the interaction terms is significant at 1% level. Overall, results support H2 and H4a. In the next paragraph I will run the same specifications but considering relative-to-competitor values and thus testing H3, and H4a and b.

Table 6. Effect of global and industrial diversification on the cash holdings-sales growth relationship.

Dependent Variable: SALES GROWTH (1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Full sample Full sample Full sample No-MNCs MNCs CASH˗TO˗ASSET_𝑡−1 0.278*** 0.215*** 0.466*** 0.333*** 0.040

(0.037) (0.039) (0.073) (0.073) (0.033) N. GEO REGIONS𝑡−1 0.002 -0.009*** 0.007*

(0.002) (0.001) (0.004) CASH_𝑡−1∗ N. GEO REGIONS_𝑡−1 -0.066*** -0.119***

(0.010) (0.021)

N. SEGMENTS_𝑡−1 0.004* 0.012*** 0.020** 0.023*** 0.001 (0.002) (0.003) (0.008) (0.008) (0.003) CASH𝑡−1∗ N. SEGMENTS𝑡−1 -0.060*** -0.150*** -0.108*** 0.005

(0.019) (0.040) (0.036) (0.019) N. GEO REGIONS𝑡−1∗ N. SEGMENTS𝑡−1 -0.004*

(0.002) CASH_𝑡−1∗ N. REG._𝑡−1∗ N. SEGM._𝑡−1 0.043***

(0.012) SALES GROWTH𝑡−1 0.105*** 0.107*** 0.104*** 0.111*** 0.074*** (0.013) (0.013) (0.013) (0.019) (0.015) SIZE_𝑡−1 -0.025*** -0.025*** -0.025*** -0.034*** -0.020*** (0.002) (0.002) (0.002) (0.004) (0.001) TOBIN′_{S Q} 𝑡−1 0.031*** 0.031*** 0.031*** 0.029*** 0.036*** (0.003) (0.003) (0.003) (0.004) (0.003) FIXED ASSET GROWTH𝑡−1 0.126*** 0.127*** 0.126*** 0.133*** 0.125***

(0.010) (0.010) (0.010) (0.016) (0.011) CAPEX𝑡−1 0.101* 0.098* 0.103* 0.164* -0.064 (0.058) (0.058) (0.058) (0.094) (0.066) SELLING EXPENSES_𝑡−1 -0.165*** -0.167*** -0.166*** -0.138*** -0.190*** (0.014) (0.014) (0.014) (0.024) (0.016) LEVERAGE𝑡−1 0.028** 0.031** 0.026* 0.066*** -0.018 (0.014) (0.014) (0.014) (0.025) (0.012) R&D_𝑡−1 0.321*** 0.325*** 0.298*** 0.440*** 0.042 (0.068) (0.070) (0.069) (0.131) (0.060) ANTI˗SELF˗DEALING_𝑘 0.019* 0.016 0.020* 0.035 0.024** (0.010) (0.010) (0.010) (0.025) (0.010) Constant 0.388*** 0.402*** 0.364*** 0.427*** 0.357*** (0.032) (0.032) (0.034) (0.064) (0.035) Observations 40,746 40,746 40,746 14,013 26,733

Year fixed effects Yes Yes Yes Yes Yes

Country fixed effects No No No No No

Industry fixed effects Yes Yes Yes Yes Yes

R-squared 0.167 0.166 0.168 0.156 0.176

Table 7. Effect of global and industrial diversification on the cash holdings-market share growth relationship. Dependent Variable: MKT SHARE

GROWTH

(1) (2) (3) (4) (5)

OLS OLS OLS OLS OLS

Full sample Full sample Full sample No-RC_MNCs RC_MNCs zCASH𝑡−1 0.019*** 0.019*** 0.018*** 0.013* 0.026*** (0.006) (0.006) (0.006) (0.007) (0.008) RC_N. GEO REGIONS𝑡−1 -0.006 -0.006 -0.004 (0.004) (0.004) (0.004) zCASH_𝑡−1∗ RC_N. REG._𝑡−1 0.013*** 0.014*** (0.005) (0.005) RC_N. SEGMENTS_𝑡−1 0.011* 0.012** 0.013** 0.016** 0.010 (0.006) (0.006) (0.006) (0.007) (0.009) zCASH_𝑡−1∗ RC_N. SEGM._𝑡−1 0.014** 0.010 0.000 0.027** (0.007) (0.006) (0.008) (0.011) RC_N. REG._𝑡−1∗ RC_N. SEGM._𝑡−1 -0.002 (0.006) zCASH_𝑡−1∗ RC_N. REG._𝑡−1∗ RC_N. SEGM._𝑡−1 0.021***

(0.007) MKT SHARE GROWTH𝑡−1 0.074*** 0.074*** 0.074*** 0.070*** 0.075*** (0.009) (0.009) (0.009) (0.012) (0.014) RC_SIZE_𝑡−1 -0.037*** -0.037*** -0.037*** -0.041*** -0.037*** (0.005) (0.005) (0.005) (0.006) (0.007) RC_TOBIN′_{S Q} 𝑡−1 0.026*** 0.026*** 0.026*** 0.024*** 0.030*** (0.005) (0.005) (0.005) (0.007) (0.008) RC_FIXED ASSET GROWTH_𝑡−1 0.065*** 0.065*** 0.065*** 0.064*** 0.066***

(0.005) (0.005) (0.005) (0.007) (0.008) RC_CAPEX_𝑡−1 0.421** 0.420** 0.423** 0.488** 0.256 (0.172) (0.172) (0.172) (0.212) (0.290) RC_SELLING EXPENSES_𝑡−1 -0.164*** -0.163*** -0.163*** -0.124*** -0.239*** (0.037) (0.037) (0.037) (0.045) (0.061) RC_LEVERAGE𝑡−1 0.045 0.043 0.044 0.046 0.067 (0.037) (0.037) (0.037) (0.046) (0.060) RC_R&D_𝑡−1 1.180*** 1.176*** 1.172*** 0.695*** 2.116*** (0.169) (0.169) (0.169) (0.215) (0.265) ANTI˗SELF˗DEALING𝑘 -0.131*** -0.130*** -0.131*** -0.156*** -0.086* (0.032) (0.032) (0.032) (0.039) (0.046) Constant 0.255*** 0.258*** 0.258*** 0.290*** 0.199*** (0.043) (0.043) (0.044) (0.068) (0.054) Observations 40,746 40,746 40,746 24,390 16,356

Year fixed effects Yes Yes Yes Yes Yes

Country fixed effects No No No No No

Industry fixed effects Yes Yes Yes Yes Yes

R-squared 0.171 0.170 0.171 0.156 0.199

their rivals (0.013, column 4; although the difference between these two coefficients appears not statistically significant). In column 3, global and industrial diversification are considered jointly. In line with H4b, the positive and significant coefficient supports the idea that the two diversification dimensions reinforce each other’s effect in moderating the relationship between cash holdings and market share growth. In particular, implementing both diversification dimensions strengthen the positive effect of cash reserves more than implementing only one of them. The same implication can be derived from columns 4 and 5. Higher levels of relative-to-competitor industrial diversification strengthen the positive effect that cash holdings have on market share growth more in companies with higher global diversification (column 5) than in more concentrated ones (column 4) and the difference is significant at 5% level.

In conclusion, results prove that company diversification is a relevant issue and has to be taken into account when analyzing the effect of cash holdings on product market performance. In absolute values, a higher level of diversification, either industrial or geographical, will weaken the positive effect that cash holdings have on sales growth, as predicted in H2. Conversely, in line with H3, being more diversified than competitors strengthens the positive effect that holding more cash than rivals have on market share growth. Finally, results support H4a when sales growth is used as measure of market performance, while H4b is supported in relative-to-competitor terms. Taken together, the analyses of the joint effect of both diversification dimensions lead to the idea that, for a company which is already diversified in one dimension, it is a good strategy to diversify also in the other one in order to maximize the benefits of cash holdings on market performance.

4.3. Investor protection

Table 8. The effect of investor protection on the cash-sales growth relationship Dependent Variable: SALES

GROWTH

(1) (2) (3) (4)

OLS OLS OLS OLS

CASH˗TO˗ASSET_𝑡−1 0.135*** -0.001 0.135*** 0.137*** (0.021) (0.080) (0.021) (0.036) ANTI˗SELF˗DEALING_𝑘 0.015 -0.016 (0.010) (0.018) CASH_𝑡−1∗ ANTI˗SELF˗DEALING_𝑘 0.208* (0.124) CREDITOR RIGHTS𝑘 0.004** 0.004 (0.002) (0.003)

CASH_𝑡−1∗ CREDITOR RIGHTS_𝑘 -0.001

(0.019) SALES GROWTH𝑡−1 0.107*** 0.107*** 0.107*** 0.107*** (0.013) (0.013) (0.013) (0.013) SIZE𝑡−1 -0.025*** -0.025*** -0.025*** -0.025*** (0.002) (0.002) (0.002) (0.002) TOBIN′_{S Q} 𝑡−1 0.031*** 0.031*** 0.032*** 0.032*** (0.003) (0.003) (0.003) (0.003) FIXED ASSET GROWTH_𝑡−1 0.127*** 0.127*** 0.127*** 0.127***

(0.010) (0.010) (0.010) (0.010) CAPEX𝑡−1 0.096* 0.095 0.093 0.093 (0.058) (0.058) (0.058) (0.058) SELLING EXPENSES_𝑡−1 -0.167*** -0.168*** -0.167*** -0.167*** (0.014) (0.014) (0.014) (0.014) LEVERAGE𝑡−1 0.032** 0.032** 0.036** 0.036** (0.014) (0.014) (0.014) (0.014) R&D𝑡−1 0.346*** 0.349*** 0.349*** 0.349*** (0.070) (0.070) (0.070) (0.069) N. GEO REGIONS_𝑡−1 -0.009*** -0.009*** -0.010*** -0.010*** (0.001) (0.001) (0.001) (0.001) N. SEGMENTS_𝑡−1 0.004** 0.004** 0.004* 0.004* (0.002) (0.002) (0.002) (0.002) Constant 0.414*** 0.434*** 0.421*** 0.421*** (0.033) (0.034) (0.031) (0.031) Observations 40,746 40,746 40,727 40,727

Year fixed effects Yes Yes Yes Yes

Country fixed effects No No No No

Industry fixed effects Yes Yes Yes Yes

R-squared 0.166 0.166 0.166 0.166

Table 9. The effect of investor protection on the cash-market share growth relationship Dependent Variable: MKT SHARE

GROWTH

(1) (2) (3) (4)

OLS OLS OLS OLS

zCASH_𝑡−1 0.018*** -0.017 0.018*** 0.017 (0.006) (0.020) (0.006) (0.011) ANTI˗SELF˗DEALING_𝑘 -0.130*** -0.131*** (0.032) (0.032) zCASH_𝑡−1∗ ANTI˗SELF˗DEALING_𝑘 0.054* (0.032) CREDITOR RIGHTS𝑘 0.034*** 0.034*** (0.006) (0.006)

zCASH_𝑡−1∗ CREDITOR RIGHTS_𝑘 0.000

(0.006) MKT SHARE GROWTH𝑡−1 0.074*** 0.074*** 0.074*** 0.074*** (0.009) (0.009) (0.010) (0.010) RC_SIZE𝑡−1 -0.037*** -0.037*** -0.037*** -0.037*** (0.005) (0.005) (0.005) (0.005) RC_TOBIN′_{S Q} 𝑡−1 0.026*** 0.026*** 0.026*** 0.026*** (0.005) (0.005) (0.005) (0.005) RC_FIXED ASSET GROWTH_𝑡−1 0.065*** 0.065*** 0.065*** 0.065***

(0.005) (0.005) (0.005) (0.005) RC_CAPEX𝑡−1 0.420** 0.420** 0.418** 0.418** (0.172) (0.172) (0.173) (0.173) RC_SELLING EXPENSES_𝑡−1 -0.164*** -0.164*** -0.166*** -0.166*** (0.037) (0.037) (0.036) (0.036) RC_LEVERAGE𝑡−1 0.043 0.043 0.044 0.043 (0.037) (0.037) (0.037) (0.037) RC_R&D𝑡−1 1.177*** 1.177*** 1.139*** 1.139*** (0.169) (0.169) (0.168) (0.167) RC_N. GEO REGIONS_𝑡−1 -0.006 -0.006 -0.006 -0.006 (0.004) (0.004) (0.004) (0.004) RC_N. SEGMENTS_𝑡−1 0.010* 0.010* 0.010* 0.010* (0.006) (0.006) (0.006) (0.006) Constant 0.256*** 0.256*** 0.079** 0.079** (0.043) (0.044) (0.040) (0.040) Observations 40,746 40,746 40,727 40,727

Year fixed effects Yes Yes Yes Yes

Country fixed effects No No No No

Industry fixed effects Yes Yes Yes Yes

R-squared 0.170 0.170 0.171 0.171

This table shows how the level of financial market development moderates the impact that cash holdings have on firms’ product market performance, represented by market share growth. The strength of a country investor protection is proxied by ANTI-SELF-DEALING (in columns 1 and 2) and CREDITORS RIGHTS (in 3 and 4). Standard error in parenthesis are clustered at the firm-level. The sample period is 2002-2017. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

CREDITOR RIGHTS is used as proxy of investor protection, there is no evidence for the coefficient of the interaction term to be statistically different from zero. In unreported tables, I use the level of domestic credit to private sector by banks as percentage of GDP (FINANCIAL CREDIT) as measure of financial development and run WLS regressions for all three proxies: results show that the coefficient of the interaction term is not significant. Overall, results are not sufficient to confirm the implication of H5, suggesting that the level of investor protection does not affect the relationship between cash holdings and sales growth.

In conclusion, Table 9 aims at testing the implications of H6, according to which the strength of a country’s investor protection weakens the positive effect of cash holdings on market share growth. Similar to the previous table, I first test the model where the country-level variable is ANTI-SELF-DEALING and CREDITOR RIGHTS. Against predictions, column 2 reports a positive and (weakly) significant coefficient of the interaction term, suggesting that higher levels of investor protection strengthen the positive effect of cash holdings on market share growth. As suggested in H5, the result could be explained by the fact that stronger shareholder protection leads to higher growth opportunities and better allocation of resources. If companies are able to use their superior liquidity to foster market share growth at the expense of their rivals, they should be able to do it even more effectively in a country with strong investor protection. However, this finding is not supported by results in column 4, where the interaction term results non-significant. Similarly, when I use FINANCIAL CREDIT as country-level factor, as well as with WLS regressions, the coefficient of the interaction term does not statistically differ from zero, leading to the conclusion that investor protection does not affect the relationship between holding more cash than competitors and market share growth.

5. Conclusion

market performance, considering a world-wide sample. Moreover, this thesis studies how the main relationship is influenced by companies’ diversification and country-level investor protection.

The empirical analysis suggests that there is a positive relationship between cash holdings and market performance: higher levels of liquid reserves enables companies to more readily capture growth opportunities. Thus, managers who are willing to experience higher sales growth and market share growth should increase the volume of liquid reserves and keep a more liquid position than competitors. Furthermore, I consider the role played by diversification in the main relationship. On the one hand, results suggest that diversification reduces the positive effect of cash holdings on sales growth. The higher complexity and diversity caused by a diversification strategy reduce the efficient use of liquid reserves. However, implementing both diversification dimensions does not result in even weaker effect of cash holdings on sales growth. On the other hand, diversification is also responsible for strategic advantages in terms of market competition. Companies with a degree of diversification higher than the one of competitors obtain knowledge and skills that enable them to increase the advantages from their superior liquidity and further increase their market share. This effect is even stronger in a strategy that includes both diversification dimension. Thus, to maximize the positive effect of cash reserves on sales growth, companies should limit their level of diversification. However, when they are able to diversify more than their competitors and have a stronger financial position, they should implement a diversification strategy which will increase the benefits of their liquidity in terms of market share growth. Moreover, when a company is already diversified in one dimension, a further diversification in the other dimension appears to be an efficient strategy both in terms of sales growth and market share growth. Finally, the country where the company is located seems to play only a marginal role in determining the effect of cash on market performance. Results do not support the idea that the country level of investor protection significantly moderates the effect that cash holdings have on both sales growth and market share growth.

6. Appendices Appendix A

Table 10. Variable definition

Variable Definition

SALES GROWTH Percentage change in total sales between one year and the previous one.

MKT SHARE GROWTH Sales Growth - Country-Industry-Year average Sales Growth; where the industry is identified by two-digit SIC code.

CASH-TO-ASSET Cash and short-term investments over book value of total asset.

ZCASH (Cash-to-asset – year average of cash-to-asset) / country-industry-year standard deviation of cash-to-asset; where the industry is identified by two-digit SIC code.

SIZE Natural logarithm of book value of asset in USD.

TOBIN’S Q (Total asset – book value of equity + market value of equity) / total assets. in particular, I calculated book value as the book value per share * number of outstanding shares. FIXED ASSET GROWTH Growth rate of property, plant and equipment.

CAPEX Capital expenditures scaled by book value of total assets.

SELLING EXPENSES Selling general and administrative expenditures divided by book value of total assets. LEVERAGE Long-term debt divided by book value of total asset.

R&D Research and development expenditures divided by book value of total asset.

N. GEO REGIONS Number of different geographic regions in which the company operates. It can assume values from one to ten. Data are provided by Worldscope (WC19601 to WC19691). N. SEGMENTS Number of different product segment in which the company operates where the

industry segment is identified by two-digit SIC code. It can assume values from one to ten. Data are provided by Worldscope (WC19601 to WC19691).

MNC It is a dummy variable that takes the value of one when the company operates in more than one geographic region.

RC_MNC A dummy variable that takes the value of one when the company operates in more geographic regions than its competitors.

ANTI-SELF-DEALING The anti-self-dealing index is developed by Djankov et al. (2008) and captures the strength of the regulation that protect minority shareholders within a country. It is the combination of an ex-ante anti-self-dealing index, which represents the strength of anti-self-dealing laws, and an ex-post anti-self-dealing index, which represents the enforcement of these laws.

CREDITOR RIGHTS The creditor rights index is developed by Djankov, McLiesh, and Shleifer (2007). It ranges from zero to four and a higher score represents stronger creditor rights. It aggregates four dimensions of creditors rights (creditors restrictions, capacity to seize collateral, secured creditors are payed first, management does not retain administration of its property pending the resolution of the reorganization) and a country receives one point for each dimension that it secures.

FINANCIAL CREDIT It’s a time-variant country-level factor which represents the level of domestic credit to private sector by banks as percentage of GDP. Data are provided by the World Bank [https://data.worldbank.org/indicator/FD.AST.PRVT.GD.ZS].

ASSET TANGIBILITY (0.715*receivables plus 0.547*Inventories plus 0.535*fixed capital) / book value of total asset.

Appendix B

Table 11. 2SLS regression of cash holdings on sales growth Dependent Variable: SALES

GROWTH (1) (2) (3) (4) 2SLS 2SLS 2SLS 2SLS CASH˗TO˗ASSET𝑡−1 0.230*** 0.227*** 0.232*** 0.228*** (0.029) (0.028) (0.028) (0.028) SALES GROWTH𝑡−1 0.103*** 0.106*** 0.108*** 0.106*** (0.014) (0.014) (0.014) (0.014) SIZE_𝑡−1 -0.026*** -0.023*** -0.026*** -0.023*** (0.002) (0.002) (0.002) (0.002) TOBIN′_{S Q} 𝑡−1 0.029*** 0.029*** 0.029*** 0.029*** (0.003) (0.003) (0.003) (0.003) FIXED ASSET GROWTH_𝑡−1 0.127*** 0.127*** 0.128*** 0.127***

(0.010) (0.010) (0.010) (0.010) CAPEX_𝑡−1 0.114* 0.125** 0.145** 0.129** (0.060) (0.060) (0.060) (0.060) SELLING EXPENSES_𝑡−1 -0.161*** -0.164*** -0.167*** -0.163*** (0.013) (0.013) (0.013) (0.013) LEVERAGE𝑡−1 0.069*** 0.047*** 0.050*** 0.048*** (0.015) (0.014) (0.015) (0.014) R&D_𝑡−1 0.265*** 0.239*** 0.235*** 0.240*** (0.074) (0.073) (0.073) (0.073) N. GEO REGIONS𝑡−1 -0.009*** -0.009*** (0.001) (0.001) N. SEGMENTS_𝑡−1 0.005** 0.005** (0.002) (0.002) ANTI˗SELF˗DEALING_𝑘 0.016 0.022** 0.016 (0.010) (0.010) (0.010) Constant 0.351*** 0.389*** 0.388*** 0.383*** (0.058) (0.034) (0.033) (0.034) Observations 40,497 40,497 40,497 40,497

Year fixed effects Yes Yes Yes Yes

Country fixed effects Yes No No No

Industry fixed effects Yes Yes Yes Yes

R-squared 0.169 0.166 0.165 0.166

Partial R-squared (first-stage regression)

0.670 0.678 0.678 0.678

Table 12. 2SLS regressions of cash holdings on market share growth Dependent Variable: MKT SHARE

GROWTH (1) (2) (3) (4) 2SLS 2SLS 2SLS 2SLS zCASH𝑡−1 0.042*** 0.040*** 0.041*** 0.041*** (0.008) (0.008) (0.008) (0.008) MKT SHARE GROWTH𝑡−1 0.057*** 0.074*** 0.074*** 0.074*** (0.009) (0.009) (0.009) (0.009) RC_SIZE_𝑡−1 -0.034*** -0.033*** -0.037*** -0.035*** (0.004) (0.004) (0.004) (0.005) RC_TOBIN′_{S Q} 𝑡−1 0.023*** 0.024*** 0.024*** 0.024*** (0.005) (0.005) (0.005) (0.005) RC_FIXED ASSET GROWTH_𝑡−1 0.064*** 0.066*** 0.066*** 0.066***

(0.005) (0.005) (0.005) (0.005) RC_CAPEX_𝑡−1 0.468*** 0.446** 0.462*** 0.457*** (0.168) (0.174) (0.174) (0.174) RC_SELLING EXPENSES_𝑡−1 -0.165*** -0.161*** -0.162*** -0.160*** (0.039) (0.037) (0.037) (0.037) RC_LEVERAGE𝑡−1 0.063* 0.068* 0.070* 0.068* (0.037) (0.038) (0.038) (0.038) RC_R&D_𝑡−1 0.973*** 1.106*** 1.108*** 1.108*** (0.171) (0.173) (0.173) (0.173) RC_N. GEO REGIONS𝑡−1 -0.006 -0.006 (0.004) (0.004) RC_N. SEGMENTS_𝑡−1 0.011* 0.012* (0.006) (0.006) ANTI˗SELF˗DEALING_𝑘 -0.130*** -0.129*** -0.130*** (0.032) (0.032) (0.032) Constant 0.134* 0.257*** 0.256*** 0.257*** (0.072) (0.044) (0.043) (0.043) Observations 40,497 40,497 40,497 40,497

Year fixed effects Yes Yes Yes Yes

Country fixed effects Yes No No No

Industry fixed effects Yes Yes Yes Yes

R-squared 0.184 0.171 0.171 0.171

Partial R-squared (first-stage regression)

0.570 0.571 0.570 0.570

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