# Empirical research on mergers’ leverage dynamics and post-merger integration duration

Yao Cheng (BLCU Youth Talent Development Programme, Business School, Beijing Language and Culture University, Beijing, China)

ISSN: 0307-4358

Publication date: 3 July 2019

## Abstract

### Purpose

The purpose of this paper is to examine the effects of the post-merger integration duration on acquiring firms’ leverage behavior before and after a merger, using a dynamic model in which full merger benefits cannot be consumed at the instant of a merger, but rather after a pre-specified post-merger integration period.

### Design/methodology/approach

This paper presents a dynamic model and empirical tests that describe the impact of the post-merger integration period on the capital structure dynamics of the acquiring and target ﬁrms prior to a merger and during the post-merger integration period. By incorporating costs associated with the post-merger integration period, the model can provide new implications for the leverage behavior around the merger.

### Findings

Empirical tests support the model implications by showing that the longer the expected post-merger integration process, the less likely the acquirer will structure the financing of the combined firm in a manner that increases firm leverage. Since integration takes time to complete, an acquirer tends to retain financial flexibility during the integration process by assuming lower levels of debt when determining the capital structure of the merged entity.

### Originality/value

The model generates new implications related to acquiring firms’ leverage dynamics along with the method of payment choice. The analysis of the duration of the post-merger integration period extends both the theoretical and empirical literature that tacitly assumes that the merger-related synergy is realized immediately at the merger date. This is the first model in the literature that assumes that both the acquiring and the target firms can change their capital structure overtime, which allows us to analyze both the financing structure and the merger timing. Previous empirical studies also ignore the integration period in the analysis of the method of payment choice and leverage behavior around mergers. The model in this paper can be extended along a number of dimensions.

## Keywords

#### Citation

Cheng, Y. (2019), "Empirical research on mergers’ leverage dynamics and post-merger integration duration", Managerial Finance, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MF-05-2018-0196

### Publisher

:

Emerald Publishing Limited

## 1. Introduction

### 1.1 Research objectives

The integration of two merging ﬁrms takes time to complete. We refer to this time lag between the initiation of the merger and its completion as the “post-merger integration duration” (PMID). This means that the synergy gains from the merger cannot be captured instantly at the merger date but rather only after the ﬁrms go through an integration/transition period. This period is often associated with temporarily higher costs and an elevated uncertainty about the merger success. Only after the post-merger integration is complete, can the newly merged ﬁrm fully enjoy the merger beneﬁts. This merger integration period receives a great deal of attention among practitioners, but is largely ignored in both the theoretical and empirical literature on mergers. Annual reports of acquiring ﬁrms frequently discuss the challenges and difficulties ﬁrms may face during the integration period, such as possible problems in maintaining key employees, consolidating and rationalizing corporate infrastructures and eliminating redundant processes. There have been numerous reports of culture clashes, confusion and internal disruptions leading to declines in employee and customer satisfaction and loss of proﬁtability. For these reasons, companies that expect a longer post-merger integration period may face temporarily higher expenses spread over a longer period coupled with higher operating risk. In turn, this expectation of long integration duration should directly affect an acquirer’s decision when to merge, how to pay and most importantly the capital structure of the newly merged ﬁrm.

### 1.2 Content

This paper examines the effects of the PMID on acquiring ﬁrms’ leverage behavior before and after a merger, using a dynamic model in which full merger beneﬁts cannot be consumed at the instant of a merger, but rather after a pre-speciﬁed post-merger integration period. The model is built in continuous time with an inﬁnite horizon framework that describes the leverage dynamics of two ﬁrms: the acquirer and the target. Each ﬁrm continuously generates earnings which depend on the price of its own product and its respective ﬁxed production costs and taxes, which depend on the level of debt. The model implies that because earnings do not increase instantly upon the merger, there is no immediate need for additional tax shields, which can explain why ﬁrms that expect a longer integration period tend to use less debt. It should be stressed that the presence of the PMID is the necessary condition for optimal ratios being lower for the periods immediately following the merger.

The empirical section of the paper documents evidence that supports the model implications that the duration of the post-merger integration process signiﬁcantly affects the leverage behavior of the merged ﬁrm before and after the year of merger. Starting with the universe of mergers that took place between 1999 and 2017, we select mergers in which we can gather data on the expected time for merger-related gains to materialize. Using this method, we come up with a sample of 3,120 mergers in which we can create the variable for the expected integration duration. For the sample we create a variable that measures the PMID. Speciﬁcally, for each merger, we manually read each 10-K ﬁling, 8-K ﬁling and merger-related proxy statements on Edgar Online and news stories from FACTIVA and search for information about the estimated timeline of cost savings and/or revenue enhancements. Because the model endogenizes both the capital structure decisions and the merger timing, it can also offer a rationale for several time-series observations around mergers.

### 1.3 Innovation points of the research

The model generates new implications related to acquiring ﬁrms’ leverage dynamics along with the method of payment choice. The analysis of the duration of the post-merger integration period extends both the theoretical and empirical literature that tacitly assumes that the merger-related synergy is realized immediately at the merger date.

This is the ﬁrst model in the literature that assumes that both the acquiring and the target ﬁrms can change their capital structure overtime, which allows us to analyze both the ﬁnancing structure and the merger timing. For example, the related model in Morellec and Zhdanov’s (2008) study presents the interaction between ﬁnancial leverage and bidding contest. In their model, capital structure plays a role of a commitment device, which only determines the outcome of the acquisition contest, where the merger-related proﬁts are realized immediately at the instant of merger. By contrast, our model predicts that the leverage of the winning bidder should be below the industry average and that acquirers should lever up after the takeover. These implications resonate with the implications of our model but they are based on different mechanisms.

Previous empirical studies also ignore the integration period in the analysis of the method of payment choice and leverage behavior around mergers. For example, Martin (2016) examines the motives underlying the method of payment in acquisitions and ﬁnds that the likelihood of stock ﬁnancing increases with the acquirer’s growth opportunities and higher pre-acquisition market and acquiring ﬁrm stock returns. In our tests, we control for the factors mentioned above and demonstrate that the expected integration duration is not subsumed by those variables implying that it has its own power in explaining the choice of leverage and merger ﬁnancing method.

Compared with previous studies (e.g. Samitas and Kenourgios, 2007; Samitas et al., 2008; Huang et al., 2015), the model in this paper can be extended along a number of dimensions. First, we can assume that the initial bid for the target ﬁrm may not necessarily result in a successful merger due to possible bidding contests or uncertainty with respect to shareholders’ approval. Also, one can endogenize the premium that the acquirer pays to the target ﬁrm. These types of extensions, while interesting, will not change the main implications of the paper.

### 1.4 Research framework

The rest of the paper is organized as follows. In Section 2, we describe the model which offers new implications as well as economically plausible explanations to several stylized facts about the observed capital structures of mergers. In Section 3, we calculate and demonstrate valuation of target firm, merged firm and acquiring firm. In Section 4, we describe the base case parameters of the model. In Section 5, we test several predictions derived from the model. Section 6 concludes the model and empirical evidence on mergers’ leverage and post-merger duration.

## 2. Description of the model

### 2.1 The earnings of the acquiring firm and the target firm

The acquirer and the target ﬁrm continuously generate earnings by selling products whose unit market price, p1 and p2, respectively, evolve through time in the manner described by the following stochastic process:

(1) d p 1 p = ( γ α 1 ) d t + δ 1 d W 1 ,
(2) d p 2 p = ( γ α 2 ) d t + δ 2 d W 2 ,
where W1 and W2 are the Wiener processes under the risk-neutral measure Q; δ1 and δ2 the instantaneous volatility coefficients; r the risk-free rate, which is assumed to be constant; and α1 and α2 (>0) the convenience yields. The two Weiner processes are correlated, where corr (W1, W2)=ρ, and the instantaneous correlation ρ is assumed to be constant.

The ﬁrm’s instantaneous net earnings before interest and taxes (EBIT) are assumed to equal p1−c1, and p2−c2, respectively, for the acquirer and the target ﬁrm, where c1 and c2 are constants (⩾0) that describe the continuous ﬁxed production costs.

### 2.2 The net earnings of the merged firm

As soon as the acquirer, which currently sells its product at price p1, merges with the target ﬁrm, which sells its product at p2, the merged ﬁrm begins selling both products of two ﬁrms and generate earnings of p1+p2. The level of the combined production cost of the merged ﬁrm will depend on the length of the post-merger “integration period” T, over which the cost c3(τ) will gradually decline from c3(T), at the initiation of the merger, to the level of c3(0), at the end of the integration period, where τ(0<τT) is remaining time until the integration period is over. The combined production cost is assumed to be described by c 3 ( τ ) = c ¯ e θ τ / T , 0T. At the initiation of the merger, τ=T, the combined production cost is assumed to be higher than the total production costs of the two ﬁrms, i.e., c 3 ( T ) = c ¯ e θ T > C 1 + C 2 . When the integration period is over, τ=0, the production costs decline to the level below the their combined pre-merger level, i.e., c 3 ( 0 ) = c ¯ < C 1 + C 2 , and will stay at that level thereafter. Thus, during the integration period, the merged ﬁrm’s instantaneous net EBIT is p1+p2−c3(τ), if 0T, and p 1 + p 2 c ¯ thereafter.

### 2.3 Corporate taxes and dividends

For all ﬁrms, the net earnings after debt payments are taxed continuously at a constant corporate rate λ, and periodic debt coupon payments are tax deductible. The ﬁrms use their earnings to meet debt obligations and pay taxes, with any residual being paid out as a dividend. The ﬁrm’s instantaneous tax obligation equals (λ)·[p1−d1], (λ)·[p2−d2], and (λ)·[p1+p2−c3(τ)−d3] for the acquirer, the target and the merged ﬁrm, respectively, where d1, d2 and d3 are the respective coupon payments. Thus, the ﬁrms instantaneous after tax dividends are the following:

(3a) ( 1 λ ) [ p i c i d i ] , i { 1 , 2 } ,
(3b) ( 1 λ ) [ p 1 + p 2 c 3 ( τ ) d 3 ] , ( 0 < τ T ) .

### 2.4 The debt structure and recapitalization

Similar to the assumptions in the studies of Fischer et al. (1989), Leland (1998) and Titman and Tsyplakov (2015), we assume that the acquiring and the target ﬁrms and the merged ﬁrm issue perpetual coupon debt with a periodic coupon payment d1, d2 and d3, respectively. Following Leland (1998) and Tsyplakov (2008), we assume that ﬁrms can increase their debt ratio but not to decrease it. We assume that the ﬁrms can instantly increase its debt ratio by simultaneously repurchasing its total outstanding debt at its market value Di and issuing new debt with greater face value and a greater periodic coupon. For accounting purposes, we assume that the face value of the debt is F1=(d1/r), and F2=(d2/r), respectively, F3=(d3/r), which are the values of perpetual debt with a periodic coupon payment d1, d2 and d3 discounted at the risk-free rate. Speciﬁcally, when the ﬁrm changes its debt level by replacing old debt that has a face value of Fi=(di/r), with new debt that has a coupon d i ^ , and face value F i ^ = ( d i ^ / r ) , the ﬁrm has to pay transaction costs of:

(4) T C i debt = C i debt F i ^ , i { 1 , 2 , 3 } ,
where C i debt is a constant parameter for each ﬁrm i. When the ﬁrm increases its debt, it receives the net proceeds of the debt issue, which the ﬁrm uses to repurchase equity.

### 2.5 Default

We assume that the acquiring ﬁrm, the target ﬁrm and the merged ﬁrm is in distress and is forced into bankruptcy if there are insufficient earnings to meet periodic debt payments, i.e., if p1−c1<d1, p2−c2<d2 and p1+p2−c3(τ)<d3, respectively. In the event of default, the equityholders of ﬁrm i get 0 value, and the debtholders recover the liquidation value of the ﬁrm E ¯ i minus default costs C i default proportional to E ¯ i , where C i default is a constant parameter and i∈{1, 2, 3}. For simplicity, we assume that the liquidation value of the ﬁrm equals the value of the unlevered ﬁrm E ¯ i assuming that after default the ﬁrm cannot recapitalize. Thus, at default, the debt value of ﬁrm i satisﬁes D i = ( 1 C i default ) · E ¯ i for i∈{1, 2, 3}.

### 2.6 The merger transaction

We assume that when the acquirer buys the target it has to pay a premium to the equityholders of the target ﬁrm, which is proportional to the total market value of the target ﬁrm’s debt and equity Cpremium=θ·(D2+E2), where θ is a positive constant.

## 3. Valuation

### 3.1 Valuation of the equity and debt of the target firm

For the target ﬁrm, its values of debt D2 and equity E2 at any period of time are functions of the state variables which include the price of its product p2 and the level of the periodic coupon payment d2. Since, by assumption, the target ﬁrm does not know that it will be acquired, the value of its equity and debt as well as its capital structure decisions does not depend on the merger possibility. Values for D2 (p2, d2) and E2 (p2, d2) can be determined by solving stochastic control problems with boundary conditions, determined by recapitalization decisions of the equityholders. The boundary conditions divide the state space (p2, d2) into three regions: the recapitalization region, no recapitalization region and the default region. Using standard arbitrage arguments of Merton (1974), in the “no recapitalization region,” the equity value E2 (p2, d2) is given by the solution to the following PDE:

(5) E 2 ( p 2 , d 2 ) = [ E ( p 2 , d 2 ^ ) + D ( p 2 , d 2 ^ ) D ( p 2 , d 2 ) T C 2 debt ] d 2 ^ > d 2 max ,
such that E ( p 2 , d 2 ^ ) > 0 , where T C i debt are the transaction costs that were introduced earlier, D(p2, d2) and D ( p 2 , d 2 ^ ) are the market value of old and new debt, respectively. The amount D ( p 2 , d 2 ^ ) D ( p 2 , d 2 ) is paid to current equityholders for the portion of their shares that are repurchased.

### 3.2 Valuation of the equity and debt of the merged firm

The values of debt D3 and equity E3 of the merged ﬁrm are functions of the prices of two products p1 and p2, the level of the periodic coupon payment d3 and the remaining post-merger integration period τ which, in turn, determines the level of production costs c3(τ). The values for D2(p1, p2, d3, τ) and E(p1, p2, d3, τ) can be determined by solving stochastic control problems with boundary conditions associated with the ﬁrm’s recapitalization decisions and its default. In the “no recapitalization region,” the equity value E2(p1, p2, d3, τ) is given by the solution to the following PDE:

{ 12 ( σ 1 ) 2 ( p 1 ) 2 2 E 3 p 1 p 1 + 12 ( σ 2 ) 2 ( p 2 ) 2 2 E 3 p 2 p 2 + p σ 1 σ 2 2 E 3 p 1 p 2 + ( γ α 1 ) p 1 E 3 p 1 + ( γ α 2 ) p 2 E 3 p 2 E 3 γ γ E 3 + ( 1 λ ) ( p 1 p 2 c 3 ( τ ) d 3 ) = 0 0 < τ T , i .e . the merger firm is still in its " integration period " 12 ( σ 1 ) 2 ( p 1 ) 2 2 E 3 p 1 p 1 + 12 ( σ 2 ) 2 ( p 2 ) 2 2 E 3 p 2 p 2 + p σ 1 σ 2 2 E 3 p 1 p 2 + ( γ α 1 ) p 1 E 3 p 1 + ( γ α 2 ) p 2 E 3 p 2 γ E 3 + ( 1 λ ) ( p 1 p 2 c ¯ d 3 ) = 0 τ = 0 , the integration period is over .

The payout ﬂow (1−λ) (p1−p2−c3(τ)−d3) is the ﬁrm’s instantaneous after tax dividends, where c 3 ( τ ) = c ¯ e θ τ is the cost during the integration period. The derivative term ( E 3 / γ ) in the ﬁrst equation represents a linear decrease in the remaining integration period τ, when 0T. The description of the boundary conditions is similar to the description in the previous section. The ﬁrm recapitalizes from debt with coupon d3 to some, d 3 ^ ( d 3 < d 3 ^ ) only if the net increase in equity value exceeds transaction costs, and its equity must satisfy:

(6) E 3 ( p 1 , p 2 , d 3 , τ ) = [ E 3 ( p 1 , p 2 , d 3 , ^ τ ) + D 3 ( p 1 , p 2 , d 3 , ^ τ ) D 3 ( p 1 , p 2 , d 3 , τ ) T C 3 debt ] d 3 ^ > d 3 max ,
for any p 1 , p 2 , d 3 , d 3 ^ , and τ such that E 3 ( p 1 , p 2 , d 3 , ^ τ ) > 0 , d 3 ^ > d 3 , where T C 3 debt is the transaction costs that were introduced earlier; D3(p1, p2, d3, τ) and D 3 ( p 1 , p 2 , d 3 , ^ τ ) the market values of old and new debt, respectively. In the default region, if p1−p2−c3(τ)<d3, the equity value is 0 (Figure 1).

### 3.3 Valuation of the equity and debt of the acquiring firm

The value of equity E1 of the acquiring ﬁrm (before the merger) is a function of not only the price of its own product p1 and the level of its debt payment d2, but also of the product price p2 of the target ﬁrm and its payment d2. The value E2 can be determined by solving stochastic control problems with boundary conditions associated with the ﬁrm’s recapitalization decisions, its merger decision and its default. If the ﬁrm is not recapitalizing, its equity value E2(p1, d1, p2, d2) is given by the solution to the following PDE:

12 ( σ 1 ) 2 ( p 1 ) 2 2 E 1 p 1 p 1 + 12 ( σ 2 ) 2 ( p 2 ) 2 2 E 1 p 2 p 2 + p σ 1 σ 2 2 E 1 p 1 p 2 + ( γ α 1 ) p 1 E 1 p 1 + ( γ α 2 ) p 2 E 1 p 2 γ E 1 + ( 1 λ ) ( p 1 c 1 d 1 ) = 0.

The ﬁrm will optimally decide to merge only if the net increase in equity value of the acquiring ﬁrm exceeds the values paid to the debtholders and equityholders of the target plus transaction costs. The acquiring ﬁrm will merger with the target as soon as:

E 1 ( p 1 , d 1 , p 2 , d 2 ) < [ E 3 ( p 1 , p 2 , d 3 ^ , T ) + E 2 ( p 2 , d 2 ) d 2 γ D 1 ( p 1 , d 1 ) d 3 ^ d 1 + d 2 max + D 3 ( p 1 , p 2 , d 3 ^ , T ) C premium ] ,
for p 1 , p 2 , d 3 ^ , such that:
E 3 ( p 1 , p 2 , d 3 ^ , T ) > 0 , E 1 ( p 1 , d 1 , p 2 , d 2 ) > E 2 ( p 2 , d 2 ) , and E 1 ( p 1 , d 1 , p 2 , d 2 ) + D 1 ( p 1 , d 1 ) > E 2 ( p 2 , d 2 ) + D 2 ( p 2 , d 2 ) ,
where E 3 ( p 1 , p 2 , d 3 ^ , T ) and D 3 ( p 1 , p 2 , d 3 ^ , T ) are the equity value and the debt values of a merged ﬁrm, the amount (d2/γ) and D1(p1, d1) are the values that paid to the debtholders of the target and the acquirer at the initiation of the merger. A value of Cpremium=θ⋅(E2(p2, d2)+D2(p2, d2)) is a premium (proportional to the value of the target) that the acquirer pays to the shareholders of the target ﬁrm. T in the value function of E3 and D3 reﬂects the fact that, at the initiation of the merger, the remaining “integration period” is T. The last two conditions account for the fact that a smaller acquirer is prohibited from acquiring a larger target, i.e. when the acquirer’s equity capitalization (i.e. its equity values) or its total value (i.e. total value of debt plus equity) are less than those of the target.

## 4. Model implications

### 4.1 Base case parameters

The model parameters are chosen to roughly match empirical observations for manufacturing ﬁrms. The volatility of the product prices σ1 and σ2 is set at 20 percent. The correlation coefficient between the two Weiner processes ρ that describe earnings of the two ﬁrms is assumed to be 0.2. The convenience yield α1 and α2 is set at 7 percent. The risk-free interest rate is set to r=7 percent, this means that the risk-neutral drift of the product prices is 0. Fixed operating costs is c1=$300 and c2=$200, i∈{1, 2}. For the base case we assume that the integration duration T is 2 years (the median value from our empirical tests that follows). We also consider comparative statics for the integration duration of T=1 and T=3 years.

### 4.2 Implications of the model for base case parameters

#### 4.2.1 Trade-offs that the acquiring ﬁrm faces in its decision to merge

The acquiring ﬁrm’s decisions are complex because the ﬁrm has to simultaneously maximize the values of two options: the option to increase its debt level and reduce its taxable income, and the timing option as to when to initiate the merger. These two options depend on the size of its own earnings p1, the level of its own debt d1 as well as the earnings of the target p2 and the target’s level of debt d2. In this decision, the acquiring ﬁrm faces trade-offs and the options affect each other. On the one hand, if the acquiring ﬁrm increases its leverage it can reduce the present value of its tax obligations. On the other hand, higher leverage will likely reduce the value of the merger option, because an acquirer with higher leverage will be less optimally prepositioned to merge. By assumption, the beneﬁts of the merger do not directly depend on the earnings size of the target ﬁrm, the acquiring ﬁrm with earnings signiﬁcantly higher than costs will not initiate a merger.

#### 4.2.2 Decision to merge

Table I reports the decision to merge/not to merge of the acquirer as a function of its earnings and the earnings of the target ﬁrm, for three different levels of its own debt payments d1=120, d1=160 and d1=180, as well for the target ﬁrm’s debt payment of d2=0, d2=40, d2=80, d2=120 and d2=160. For the variable values that are outside this range, the acquirer will not start the merger.

In Table I, we hold the earnings of the target ﬁrm constant (p2=800). The results in the table imply that the acquirer does not initiate the merger if the target ﬁrm’s debt is above 120 for any level of the target’s earnings p1. This is because the acquirer is less willing to guarantee the target’s debt if it is of a relatively large size. For example, if the earnings of the target ﬁrm are p2=800, the optimal leverage is 30 percent (d2=251). At such a level of debt, the acquiring ﬁrm will not initiate the merger. If the target ﬁrm’s leverage is 17 percent or lower (debt payment d2<85) which is signiﬁcantly below its optimal level, then the acquirer would initiate the merger. This implication of the model suggests that ﬁrms that are underleveraged are more likely become a target of acquisitions. In other words, the leverage of the target ﬁrm observed at the instant of the merger tends to be lower than the optimal leverage of similar ﬁrms. This is due to the optimal timing on the part of the acquirer that will optimally choose (or wait for) to acquire the target ﬁrm that has a lower leverage.

#### 4.2.3 The optimal leverage choice of the acquiring ﬁrm at the merger time

The optimal leverage decision of the acquiring ﬁrm is complex and it depends on the value of the merger option. Table II reports the optimal leverage of the acquirer and an otherwise identical ﬁrm that has no option to merge, as a function and its earnings p1, keeping the earnings (p2=800) and the debt level (d2=0) of the target ﬁrm constant. For example, if the otherwise identical ﬁrm has no option to merge and its earnings are p1=1,200, the optimal debt level (i.e. the leverage to which the ﬁrm would instantly recapitalize to) corresponds to 42 percent. For comparison, the acquirer’s optimal leverage is about 20 percent. This result demonstrates that, in periods prior to an acquisition, an acquiring ﬁrm will optimally choose lower leverage ratios relative to its peers. This lower leverage of the acquirer tends to be interpreted in the related literature as being driven by the managerial empire-building incentives. The model shows that, due to an anticipated delay in capturing merger-related gains, an acquiring ﬁrm should rationally preposition itself by choosing lower leverage immediately before initiating a merger.

## 5. Empirical tests

In the following sections, we test several predictions derived from the model with a particular focus on the eﬀect of integration duration on the leverage decision of the merging ﬁrms. We exclude 121 cases in which we do not have enough information to calculate one-year market-adjusted pre-merger acquirer abnormal returns and another six cases in which sales are missing in the probit regression. In the Tobit model, we exclude 9 cases in which the inverse Mill’s ratios are missing, and 12 cases in which we cannot calculate the pre-merger leverage deviation.

### 5.1 Sample description

The sample of mergers comes from the Securities Data Company’s (SDC) US Mergers and Acquisition Database. We select domestic mergers with announcement dates between 1999 and 2017[1]. We only consider mergers in which acquirers end up with full control of the target ﬁrms and we also require that the acquirers control less than 50 percent of the target before the merger announcement. We further require that the merger is completed; the acquirer and the target are not in ﬁnancial (SIC 6000–6999) and regulatory (4900–4999) industries; the acquirer is a public ﬁrm so that we have necessary Compustat data to compute relative size of target to acquirer market size; the deal value relative to the market value of the acquirer is at least 18 percent[2], to eliminate the inﬂuence of very small acquirers and very small deals, we require that acquirers’ CPI-adjusted market value of assets are larger than $10m, and the transaction value of deals in our sample is at least$19.5m. Our requirements leave us with a ﬁnal sample of 3,527 successful mergers between 1999 and 2017.

We obtain managers’ discussions about the merger deal from several data sources including annual 10-K ﬁlings, 8-K ﬁlings and merger-related proxy statements on Edgar Online and news stories from FACTIVA. In these data sources, we search for the information about managerial expectations as to when merger-related gains are expected to materialize in order to create the PMID variable. For each deal, we conduct a keyword search through the entire text of annual 10-K ﬁlings, 8-K ﬁlings and merger-related proxy statements from the ﬁscal year of merger announcement to the ﬁscal year of merger completion and identify all sections of text in which the integration process and expected merger gains are discussed. Using this approach, we are able to construct the PMID variable in 420 mergers (13.5 percent) from our initial sample. PMID ranges from 0.4 to 19 years with sample median of 2.7 years. There is some clustering with respect to the PMID variable.

Panel A of Table III reports the number of mergers in each PMID group. We ﬁnd 155 cases in which PMID=2 years. Therefore, we split the PMID subsample into three relatively even groups of PMID<2 years, PMID=2 years and PMID>2 years, as shown in the table. Panel B of Table III shows that horizontal mergers consist of 53 percent of the PMID sample, and vertical mergers and diversifying mergers are 20 and 27 percent, respectively. Panel C of Table III describes the industry distribution for mergers in which we are able to create PMID. For each one-digit Standard Industrial Classiﬁcation (SIC) code, we report the number of mergers during the entire sample period. While ﬁrms in the manufacturing industry have more observations with PMID reported, our sample is not dominated by any particular industry. Observations in each PMID group are distributed relatively evenly across industries.

### 5.2 Empirical findings

In this section we ﬁrst report summary statistics on acquirer and target ﬁrm characteristics for the whole sample and subsamples in which we are able to create PMID. Next, we examine the association between PMID and market leverage at the year of merger. Third, we examine the impact of PMID on the choice of method of payment. Fourth, we verify our results by examining the magnitude of the change in leverage around the merger that is attributable to PMID. Finally, we examine the leverage dynamics during the post-merger integration period.

#### 5.2.1 Acquirer and target ﬁrm characteristics

Table IV provides median values for selected acquirer and target ﬁrm characteristics for the initial sample and subsamples across three PMID groups.

Panel A shows that the market value of acquirers paying with equity is smaller than that of acquirers paying with cash or paying with a mix of cash and equity. The higher ratios of market-to-book assets for acquirers paying with equity suggest that these acquirers have larger growth opportunities, consistent with the studies of Martin (2016) and Harford (2015). In addition, acquirers paying with equity tend to be less proﬁtable and hold more cash. Furthermore, Panel A also shows that market leverage is much lower for equity deals. Given that acquirers paying with equity tend to have larger investment opportunities, it is likely that they hold larger cash balances and are less leveraged (i.e. Titman and Wessels, 2015). Panel A also indicates that the market value of acquirers for the PMID sample is larger than that of the sample of acquirers in which we are not able to construct PMID. This is not surprising as there is likely much more media/news coverage of larger ﬁrms. However, the market-to-book ratio of acquirers in which we can create PMID is slightly lower than that of acquirers in which we cannot construct PMID. Moreover, acquirers that have PMID are likely to be more proﬁtable, hold less cash and have higher leverage. They are in general more similar to acquirers paying with cash or with mix of cash and equity. Panel A also reports acquirer ﬁrm leverage deviations. The pre-merger leverage deviation for all deals is negative; and more negative for stock acquirers. Firms in which we are able to create PMID are on average less underleveraged than ﬁrms in which we cannot create PMID. Speciﬁcally, the median leverage deviation is −0.06 and −0.14 for the PMID sample and non-PMID sample, respectively.

Panel B presents summary statistics regarding target ﬁrm characteristics. Particularly, market size and relative size of target to acquirer are both larger for deals in which we can construct PMID. Additionally, target market leverage is higher in deals in the PMID sample.

Panel C provides information about acquirer characteristics across different PMID groups. The median market value of acquirers’ assets increases monotonically as PMID becomes longer. For example, the median market value of acquirers in PMID<2 years group is approximately $950m, while the median market value of acquirers in PMID>2 years group is approximately$5bn. In addition, the market-to-book ratio increases monotonically across PMID groups, but the differences are only marginally signiﬁcant. Furthermore, Panel B shows that market leverage, deﬁned as total book debt scaled by total market assets is 0.27 for the PMID<2 years group, 0.39 for the PMID=2 years group and 0.40 for the PMID>2 years group. Moreover, the ﬁrms with shorter PMID tend to have a larger leverage deﬁcit prior to the merger.

#### 5.2.2 Market leverage at the year of merger

In this section, we examine whether PMID is a factor in determining the leverage behavior at the year of the merger. We follow the capital structure literature and regress ﬁrm leverage on PMID and a number of factors that have been documented to impact capital structure. It is again worth noting that since we are collecting our data and creating PMID from electronic ﬁnancial ﬁlings as well as news searches on FACTIVA we are undoubtedly bound to have larger ﬁrms in our PMID sample as it is more likely that news coverage is of large established ﬁrms as opposed to smaller ones. In light of this, we study the impact of PMID on leverage determination by implementing a two-stage Heckman selection model to control for the propensity to ﬁnd managements’ statements of synergy description and thus our ability to create the PMID variable for larger ﬁrms and larger deals.

Table V reports the results of the two-stage Heckman selection model.

In the ﬁrst stage, we estimate a probit model to explain whether acquirers report PMID or not. The dependent variable is a dummy variable set equal to 1 if the acquirer reports PMID, and 0 otherwise. Since acquirer managers tend to discuss PMID in news stories when the merger is announced, we include pre-announcement ﬁscal year-end acquirer size and market-to-book ratio in the regression. To control for the possibility that acquirers are more likely to discuss PMID when they conduct acquisitions of a larger target, we include the relative size of the target to the acquirer as an independent variable. We also create a “merger type” dummy variable to control for the likelihood that the propensity to report PMID is inﬂuenced by whether the proposed merger is horizontal, vertical or diversifying. Finally, we include pre-announcement acquirer abnormal return, change in the index of leading economic indicators, speciﬁcally the change in S&P 500 index or the change in Moody’s BAA-rated bond yield during the 12 months prior to the month of merger announcement, public status of the target and announcement year dummies.

In the second stage, we use an OLS model to predict market leverage at the year of merger completion. The primary explanatory variable of interest in the regression is PMID and our hypothesis is suggests that market leverage will be negatively associated with PMID. To control for acquirer size, we include the natural logarithm of CPI-adjusted sales. Additionally, we also control for the level of pre-merger leverage level by including the acquirer and target value-weighted market leverage ratio at one year prior to the merger. We further control for the market-to-book ratio, proﬁtability, tangibility, R&D, a dividend dummy variable set equal to 1 if the ﬁrm pays a cash dividend, and two dummy variables set equal to 1 if the ﬁrm has a net operating loss carry forward or investment tax credit. Except for the level of pre-merger leverage, all other variables in the regression are contemporaneous. Finally, we control for industry effects by including the ﬁrms’ two-digit SIC code.

The result in Table V shows that PMID is signiﬁcantly negatively associated with the leverage of the combined entity at the year of merger. Furthermore, the magnitude of the coefficient on PMID indicates that this relation is not only statistically signiﬁcant, but also economically signiﬁcant. The coefficient on this variable suggest that if the post-merger integration is expected to take one additional year to complete, the market leverage at merger completion is reduced by approximately 2.92 percent. The results in Table V also show a signiﬁcant relation between leverage and other relevant control variables. As expected, a signiﬁcant positive relation exists between the pre-merger acquirer-target value-weighted market leverage and the leverage at the year of merger completion.

#### 5.2.3 Fraction mergers paid for with equity

Table VI presents the results of a two-sided Tobit model to explain the fraction of the deal paid for with equity. The dependent variable in the Tobit model is truncated at 0 and 1. To control for the probability that we are able to ﬁnd merger-related news articles (managerial statements) to construct PMID for certain deals as opposed to others, we also include the inverse Mill’s ratio estimated from the previous probit model in the regression as a regressor. Our intuition suggests that the fraction of a deal paid for with equity should be positively related to PMID. That is to say, the leverage of the newly merged ﬁrm will be lower if acquirers use more equity and less cash (debt) to ﬁnance a deal.

To control for acquirer size we include the natural logarithm of CPI-adjusted sales (in 1999 dollars). Additional control variables include the pre-merger market value-weighted acquirer and target market leverage and pre-merger market leverage deviation. Following Martin (2016), we control for market timing on the part of acquirer management (i.e. acquirer management using overvalued shares as currency in order to purchase the target) by including the market-adjusted 12-month pre-merger acquirer stock return. Speciﬁcally, we control for the change in the Standard & Poor’s 500 index or the change in the yield on Moody’s BAA-rated bonds. In addition, we include the relative size of the target to the bidder since the larger size of the target could increase the bidder’s likelihood to pay for the target with equity. Furthermore, we control for the public status of the target as this could inﬂuence the method of payment because of more information asymmetry regarding the valuation of private or subsidiary targets as these targets face a higher “liquidity discount” on the M&A market (i.e. Berkovitch and Narayanan, 2010). Finally, we also include acquirers’ pre-merger cash balance in the regression.

We implement our analysis on our initial sample and our PMID sample. The coefficient of pre-merger year leverage deviation is positively and signiﬁcantly associated with the fraction of the deal paid for with equity. However, this variable loses statistical power in our PMID sample. Consistent with our intuition, the results from show a positive association between PMID and the fraction of the merger paid for with equity. This is consistent with our hypothesis that acquirer managers are less likely to conduct leverage increasing ﬁnancing of the merger if they expect post-merger integration takes time to complete.

#### 5.2.4 Change in market leverage resulting from mergers

Our previous results demonstrate a negative relation between market leverage after the merger completion and PMID, and also a positive relation between PMID and the fraction of the deal paid for with equity. In this section, we further assure our results by analyzing the change in market leverage around the year of merger.

Table VII presents results of regressions that explain the change in leverage from year t−1 to year t (i.e. one year before merger to the year of the merger). Other than the variables included in the regression of Table VI, we also include the change in optimal leverage in each speciﬁcation. To show that PMID has additional power in explaining the leverage change before and after a merger, we include the merger-induced change leverage in the regression. In line with our hypothesis, we expect a negative relation between PMID and the actual change in market leverage from year t−1 to year t.

#### 5.2.5 Leverage dynamics during the post-merger integration period

We deﬁne the remaining PMID (RPMID) as PMID minus the number of years elapsed after a merger; therefore, RPMID ranges from 0 to initial PMID. We apply a ﬁrm ﬁxed effects model to analyze the extent to which our PMID and RPMID variables affect the leverage dynamics during the integration period, controlling for a number of conventional variables.

Table VIII reports the regression results. As expected, market leverage is negatively and signiﬁcantly associated with our PMID and RPMID variables. The magnitude of the coefficients implies that the relationship is not only statistically signiﬁcant, but also economically signiﬁcant. A one year increase in PMID leads to about a 6.9 percent decrease in a ﬁrm’s leverage during the integration period, and a one year increase of the RPMID results in about a 2.5 percent decrease in a ﬁrm’s market leverage during that period. Therefore, the evidence in this section supports our hypothesis that merged ﬁrms tend to maintain a higher degree of ﬁnancial ﬂexibility by keeping a lower level of leverage during the integration process if merger-related synergies take more time to materialize.

#### 5.2.6 Robustness of the results

Our results remain quantitatively similar if we include year dummies or if we use three-digit SIC code industries or if the PMID is 1 or 3 years. We also implement the study on our PMID sample without the Heckman two-stage speciﬁcation. The coefficient estimation of PMID is also statistically and economically signiﬁcant. We construct the fraction of the deal paid for with equity using SDC deal transaction reports. Furthermore, our results are similar if we include pre-merger market leverage of the acquirer instead of weighted average leverage of the acquirer and the target.

## 6. Conclusion

This paper provides a model and empirical evidence that the leverage behavior around mergers and during the post-merger integration period is aﬀected by the acquirer’s expectation about the length of the PMID. The model oﬀers new implications as well as economically plausible explanations to several stylized facts about the observed capital structures of mergers. The model substantiates the argument that due to anticipated delays in capturing merger-related gains, an acquiring ﬁrm should rationally preposition itself by choosing lower leverage immediately before initiating the merger and should keep a lower degree of leverage during the post-merger integration period.

Empirical tests support the model implications by showing that the longer the expected post-merger integration process, the less likely the acquirer will structure the ﬁnancing of the combined ﬁrm in a manner that increases ﬁrm leverage. Since integration takes time to complete, an acquirer tends to retain ﬁnancial ﬂexibility during the integration process by assuming lower levels of debt when determining the capital structure of the merged entity. We document that the market leverage of a newly merged ﬁrm is negatively associated with the length of the integration period. Our results also suggest that, other things being equal, acquires are more likely to ﬁnance the deal with equity when they expect a longer integration period. Finally, we show that the duration of the integration period can help explain leverage dynamics during the post-merger integration period. Overall, the model indicates that the PMID is negatively associated with the market leverage of newly merged ﬁrms at the time of merger completion and during the integration period. Further, acquirer managers are more likely to use equity to ﬁnance a merger when the integration duration is likely to be lengthy.

## Figures

#### Figure 1

Production costs of the target firm and acquiring firm before the merger, and the combined costs of the merged firm after the merger

## Table I

Decision of the acquiring firm to merge/not to merge if the post-merger integration duration is two years

Merger decision and debt decision (if merges) W-A leverage Merger decision and debt decision (if merges) W-A leverage Merger decision and debt decision (if merges) W-A leverage Merger decision and debt decision (if merges) W-A leverage W-A leverage
Debt payment of the acquiring firm Earnings of target firm Earnings of the acquiring firm Debt payment of the target firm=0 Debt payment of the target firm=40 Debt payment of the target firm=80 Debt payment of the target firm=120 Debt payment of the target firm=160
120 800 856
120 800 900
120 800 944
120 800 1,056
120 800 1,100 Merge/raise debt 0.097 Merge/raise debt 0.151 Merge/keep debt 0.196
120 800 1,144 Merge/raise debt 0.102 Merge/raise debt 0.145 Merge/keep debt 0.187
120 800 1,256 Merge/raise debt 0.101 Merge/raise debt 0.139 Merge/raise debt 0.177
120 800 1,300 Merge/raise debt 0.091 Merge/raise debt 0.132 Merge/raise debt 0.163
120 800 1,344 Merge/raise debt 0.087 Merge/raise debt 0.125 Merge/raise debt 0.158
120 800 1,456 Merge/raise debt 0.084 Merge/raise debt 0.115 Merge/raise debt 0.148
120 800 1,500 Merge/raise debt 0.076 Merge/raise debt 0.109 Merge/raise debt 0.132
120 800 1,544 Merge/raise debt 0.072 Merge/raise debt 0.103 Merge/raise debt 0.127
120 800 1,656 Merge/raise debt 0.070 Merge/raise debt 0.097
120 800 1,700
120 800 1,744
120 800 1,856
160 800 856
160 800 900
160 800 944
160 800 1,056
160 800 1,100 Merge/keep debt 0.192
160 800 1,144 Merge/raise debt 0.142 Merge/keep debt 0.186 Merge/keep debt 0.223
160 800 1,256 Merge/raise debt 0.139 Merge/raise debt 0.177 Merge/raise debt 0.217
160 800 1,300 Merge/raise debt 0.133 Merge/raise debt 0.173 Merge/raise debt 0.193
160 800 1,344 Merge/raise debt 0.127 Merge/raise debt 0.165 Merge/raise debt 0.180
160 800 1,456 Merge/raise debt 0.118 Merge/raise debt 0.161 Merge/raise debt 0.173
160 800 1,500 Merge/raise debt 0.116 Merge/raise debt 0.158 Merge/raise debt 0.161
160 800 1,544 Merge/raise debt 0.107 Merge/raise debt 0.153
160 800 1,656 Merge/raise debt 0.105
160 800 1,700
160 800 1,744
160 800 1,856
200 800 856
200 800 900
200 800 944
200 800 1,056
200 800 1,100 Merge/keep debt 0.254
200 800 1,144 Merge/keep debt 0.180 Merge/keep debt 0.213 Merge/keep debt 0.248
200 800 1,256 Merge/raise debt 0.177 Merge/raise debt 0.209 Merge/raise debt 0.236
200 800 1,300 Merge/raise debt 0.170 Merge/raise debt 0.197 Merge/raise debt 0.247
200 800 1,344 Merge/raise debt 0.168 Merge/raise debt 0.186 Merge/raise debt 0.230
200 800 1,456 Merge/raise debt 0.160 Merge/raise debt 0.177 Merge/raise debt 0.226
200 800 1,500 Merge/raise debt 0.155 Merge/raise debt 0.171 Merge/raise debt 0.215
200 800 1,544 Merge/raise debt 0.142 Merge/raise debt 0.168
200 800 1,656 Merge/raise debt 0.139
200 800 1,700
200 800 1,744
200 800 1,856

## Table II

Comparison between optimal leverage of the acquiring firm (post-merger integration duration is two years) and otherwise identical firm that has no option to merge

Earnings of the acquiring firm, p1 Optimal leverage of the acquiring firm assuming there is no option to merge Optimal leverage of the acquiring firm Merger decision of the acquiring firm
856
900
944
1,056
1,100 0.408 0.179 Merge
1,144 0.411 0.182 Merge
1,256 0.413 0.185 Merge
1,300 0.416 0.190 Merge
1,344 0.418 0.202 Merge
1,456 0.422 0.214 Merge
1,500 0.423 0.216 Merge
1,544 0.425 0.219 Merge
1,656 0.429 0.223 Merge
1,700
1,744
1,856

## Table III

PMID distribution, number of observations by industry and PMID

No. of obs. Fraction of sample
Panel A: distribution of PMID
PMID<2 122 29%
PMID=2 155 36%
PMID>2 143 34%
Panel B: number of observation by merger type
Horizontal merger 223 53%
Vertical merger 84 20%
Diversifying merger 113 27%
Panel C: number of observation by industry
SIC Industry title PMID<2 PMID=2 PMID>2
1 Mining and construction 6 5 4
2 Manufacturing (food–petroleum) 30 25 30
3 Manufacturing (plastics–electronics) 32 50 35
4 Transportation and communication 13 13 40
5 Wholesale and retail trade 14 32 19
6 Services (hotels–recreation) 21 7 13
7 Services (health–private household) 6 23 2

## Table IV

Acquirer and target characteristics

All deals Equity payment Cash or mixed With PMID Without PMID
Panel A: median acquirer characteristics
CPI-adjusted market value of assets ($mm) 436.23 315.17* 549.81*** 2,017.29*** 3,517.27 Market-to-book ratio 1.87 2.51 1.62** 1.71*** 1.91 Profitability 0.14 0.20 0.14** 0.19*** 0.12 Cash holding 0.16 0.31 0.08*** 0.07*** 0.10* Market leverage 0.30 0.25 0.36*** 0.27*** 0.24 Pre-merger leverage deviation −0.11 −0.14 −0.08*** −0.07*** −0.14 Panel B: median target characteristics CPI-adjusted market value of assets ($mm) 198.27 149.16 226.01*** 1,082.27*** 132.26
Relative size to acquirer 0.59 0.55 0.44*** 0.52** 0.51
Market leverage 0.33 0.13 0.29*** 0.30*** 0.25
Panel C: median acquirer characteristics with different integration duration
Integration period PMID<2 PMID=2 PMID>2
CPI-adjusted market value of assets (\$mm) 950.21 1,427.28*** 5,012.62**
Market-to-book ratio 1.29 1.71 1.91***
Profitability 0.15 0.14 0.16
Cash holding 0.08 0.07 0.06
Market leverage 0.31 0.31*** 0.31
Pre-merger leverage deviation −0.11 −0.07** −0.07

Notes: *,**,***Significant at 10, 5 and 1 percent levels, respectively

## Table V

Explaining market leverage after merger completion

Coefficient z-statistics
First stage: probit model of acquirers reporting PMID
Vertical merger dummy 0.152 0.92
Horizontal merger dummy 0.185 1.91
Pre-announcement market-to-book ratio 0.041 1.14
Pre-announcement CPI-adjusted acquirer sales 0.377** 9.81
Pre-announcement acquirer CAR −0.169** 1.72
Relative size of target to acquirer 0.369*** 5.71
12-month change in economic indicators −0.411 0.79
Target is a private firm dummy −0.717** 4.75
Target is a subsidiary dummy −0.507*** 3.82
Intercept −2.917** 11.28
Pseudo-R2 0.167
Number of observations 3,120
Second stage: explaining the post-merger market leverage
Pre-merger VWML 0.723** 7.19
Post-merger integration duration (PMID) −0.018*** 3.01
Tangibility −0.021 0.14
Market-to-book ratio −0.503*** 4.12
R&D −0.162 1.62
Profitability −0.481 1.37
Natural log of CPI-adjusted sales 0.002 0.24
Dividend dummy 0.053 1.85
Investment tax credit dummy −0.172** 1.73
Net operating loss carry forward dummy −0.006 0.20
Inverse Mill’s ratio −0.058 0.18
Intercept 0.417 1.93
Number of observations 409

Notes: *,**,***Significant at 10, 5 and 1 percent levels, respectively

## Table VI

Explaining the fraction of the deal paid for with equity

Whole sample PMID sample
Post-merger integration duration (PMID) 0.132*** (3.16)
Pre-merger VWML −1.151*** (3.81) 0.128 (0.23)
Pre-merger leverage deviation 0.806*** (3.19) 0.718 (1.24)
Market-to-book ratio 0.041 (0.77)
Pre-announcement acquirer CAR 0.307*** (6.05) 0.203 (1.13)
12-month change in economic indicators 0.114 (0.51) −0.527 (0.92)
Natural log of CPI-adjusted sales −0.072*** (3.00) 0.147** (1.92)
Relative size of target to acquirer 0.316*** (5.05) 0.603*** (2.92)
Cash/book asset 0.817*** (5.35) 0.902** (2.03)
Target is a private firm dummy −0.602*** (7.17) −0.911*** (2.96)
Target is a subsidiary dummy −0.512*** (4.12) −0.823*** (3.04)
Inverse Mill’s ratio 4.025** (3.01)
Intercept 1.328*** (7.01) −3.417*** (3.03)
Pseudo-R2 0.091 0.081
Number of observations 3,000 395

Notes: *,**,***Significant at 10, 5 and 1 percent levels, respectively

## Table VII

Explaining the change in market leverage around the merger

Whole sample PMID sample PMID sample
(1) (2) (3)
Post-merger integration duration (PMID) −0.030*** (2.32) −0.019** (2.03)
Pre-merger VWML −0.621 (1.13) −0.315*** (3.92) −0.126 (1.13)
Pre-merger leverage deviation −0.281** (3.15) −0.314*** (2.15)
Merger-induced change in target market leverage 0.601*** (11.28) 0.518*** (4.01)
Market-to-book ratio −0.015** (2.01) −0.024** (1.81)
Pre-announcement acquirer CAR −0.034*** (5.21) 0.002 (0.05) −0.012 (0.41)
12-month change in economic indicators 0.027 (0.61) 0.131 (1.72) 0.071 (0.91)
Natural log of CPI-adjusted sales 0.003 (0.56) −0.015 (1.19) −0.006 (0.44)
Relative size of target to acquirer 0.007 (0.79) −0.021 (1.18) −0.006 (0.51)
Cash/book asset −0.162*** (6.17) −0.401 (0.46) −0.081 (1.14)
Target is a private firm dummy 0.041*** (2.67) 0.130*** (2.40) 0.145** (2.37)
Target is a subsidiary dummy 0.068** (3.05) 0.145*** (2.23) 0.119** (1.80)
Inverse Mill’s ratio −0.501*** (2.13) −0.315* (0.82)
Intercept −0.062* (2.17) 0.610*** (2.19) 0.410 (1.27)
R2 0.209 0.181 0.271
Number of observations 2,505 272 240

Notes: *,**,***Significant at 10, 5 and 1 percent levels, respectively

## Table VIII

Explaining the leverage behavior during the post-merger integration period

(1) (2)
Post-merger integration duration (PMID) −0.081*** (3.03)
Remaining integration duration (PMID) −0.032*** (3.00)
Tangibility 0.713*** (4.05) 0.692*** (3.12)
Market-to-book ratio −0.013 (0.37) −0.012 (0.60)
R&D −0.020 (0.07) −0.051* (0.49)
Profitability −0.717*** (2.35) −0.512 (0.20)
Natural log of CPI-adjusted sales 0.031 (0.91) −0.713*** (2.43)
Dividend dummy −0.042 (1.08) −0.040 (1.14)
Investment tax credit dummy −0.034* (0.51) −0.034 (0.62)
Net operating loss carry forward dummy 0.061** (1.82) 0.050** (1.81)
Intercept 0.092 (0.41) 0.061* (0.36)
Number of observations 855 855

Notes: *,**,***Significant at 10, 5 and 1 percent levels, respectively

## Notes

1.

We only select deals in which SDC code as “Mergers” in the “form of deal” item.

2.

This condition is introduced because integration period is likely to have a material impact on the capital structure of a newly merged ﬁrm only if the acquirer and the target are of a comparable size.

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## Corresponding author

Yao Cheng can be contacted at: chengyaoblcu@163.com