The Impact of M&A on R&D of Electric Utilities

based on Heckman Two-stage Model

Jiming Tian, Tao Shen, Xin Wang and Zhichong Pan

Data Application Branch, Zhejiang Huayun Information Technology Co., Ltd., Jianghui Street, Hangzhou, China

Keywords: M&A, R&D, Electric Utilities, Heckman Two-Step.

Abstract: Electricity industry in China and abroad is undergoing profound changes, which affect the behaviours of

electric utilities in many different ways. This research empirically investigates how mergers and acquisitions

1 INTRODUCTION

With introduction of competition in wholesale and

retail electricity markets, electric utilities are taking

great efforts to adapt to the new conditions and

exploit new opportunities created by changes in

government policies toward the industry. M&A,

which plays an important role in firms’ growth and

in the electric distribution industry. During the years

affected their investments in R&D. Two measures of

R&D inputs are of interest in this analysis: R&D

The rest of the paper is organized as follow.

Section 2 is a literature review on how M&As affect

analysis about the effects of M&As on R&D. Section

4 gives an introduction about M&A and R&D in the

electric utility industry in the United States and

summary statistics of the data used in this paper.

of liberalization on R&D, and some others have

analysed the drivers of R&D spending.

2.1 Literature in the R&D-intensive

Industry

How M&As affect R&D spending is not conclusive

competitors using data on horizontal mergers among

analysed. The authors find that the overall impact of

(Denicolò, Polo, 2018) and (Federico, et al, 2017)

success but not on the value of the innovation.

(Jullien, Lefouili, 2018) discusses the effects of

annual observations for the period of 1980 to 2007.

significant effects on utilities’ R&D expenditures. By

including the M&A operation in the model, the

coefficient is positive, though it is not significant. The

author concluded that, by preventing consolidations

of the larger firms, competition commissions may

institutional changes, and political constraints on the

decline in R&D. In the selection equation, the authors

included a dummy to control for pending mergers.

significant and negative impacts on the probability of

firms’ deciding to engage in R&D.

3 THEORETICAL ANALYSIS

3.1 Characteristics of R&D

The unique characteristics of R&D investment make

it difficult to finance (Damanpour 2020). Firstly,

(Jalonen 2012). Secondly, the benefits associated

by the investors. Knowledge as the output of

the knowledge secret. Therefore, private firms tends

perfect.

3.2 Effects of M&A

In the absence of fully functioning markets for

innovation, the aggregation of end-product market

enables spreading of the costs of research over a

lower cost of capital, stronger credit profile and

of deals, merger types (i.e. merger between electric

independent power producers, merger between

the mergers between electric utilities.

utility will make positive investment, otherwise the

utility will make zero investment. The benefit of such

complying to regulatory rules. The decision equation

takes the following form:

This second equation is to examine the factors that

by the R&D expenditure and R&D intensity. The

equation takes the following form:

where 𝑣

6.1 Empirical Model Specification

Stage 1: Selection Model

(4)

(5)

Stage 2: Level Model:

Given that the utility has decided to undertake R&D

investment, this stage investigates the factors that

influence the magnitude of R&D spending.

expenditure, which is measured in 2005 dollars, or

R&D intensity. Buyer denotes the subset of utilities

who are buyers in M&As. It takes the value of 1for

the entire time period if a utility is a buyer in a

merger. Similarly, Target denotes the subset of

utilities who are targets in M&As. It takes the value

of 1 for the entire period if a utility is a target in a

merger. All observations on non-merging utilities

variable. If a utility involved in a merger in year t, the

(IMR, 𝜆

is

utilities, while Column (b) compares all targets to

This variable may be picking up the effects of

competition. The competition pressures may induce

the electric distribution utilities to reduce costs by

disengage themselves from R&D investment.

a. Standard errors in brackets; b. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01

The coefficients on Buyers is positive and that on

three models. The positive sign means those utilities

are more likely to undertake R&D, and the negative

sign means those utilities are less likely to undertake

R&D. However, both of them are not significant and

show that Buyers and Target are as likely to

coefficients are not significant and I would rather to

believe that M&As have no impact on the utilities’

decision to invest in R&D. The coefficient on

MultiMerger is negative in all three models and

significant at 10 percent level in Column (c). The

negative sign means that frequent M&As would

R&D. Since the coefficient is significant in Column

(c), it shows that frequent M&As have distracted the

management’s attention from inner development and

R&D but also positively affect the magnitude of

management strategies. This finding has an important

policy implementation. That is, the government or

regulator could come out with some appropriate

policies to induce or force the utilities to undertake

a. Standard errors in brackets; b. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01

Table 4 shows the results of the impact of M&As

Table 3. The coefficients on Buyer and Target are

the utilities that were involved into M&As during the

sample period are those with lower level of R&D

mergers have no significant impact on R&D

The empirical analysis explores an unbalanced panel

dataset consisting of 125 electric utilities during 20

to undertake R&D investment is modelled as a two-

undertake R&D investment as non-merging utilities.

But the amount of R&D investment and R&D

multiple mergers negatively affected the utilities’

probabilities to undertake R&D. But multiple-

mergers had no significant impact on the amount of

Bourreau, M. & Jullien, B. 2018. Mergers, investments and

demand expansion. Economics Letters, 167(136-141.

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systematic review of the literature. Journal of

Restructuring, competition, and R&D in the US electric

Wooldridge, J. M. 2010. Econometric analysis of cross