Page 99 - Contributed Paper Session (CPS) - Volume 5

CPS1111 Jitendra Kumar et al.
financial institutions are continuously working as well as growing well but
there are few firms which are not efficiently operating as per
public/state/owner’s need and may be acquired or possibly consolidated by
other strong company. This may be due to not getting high-quality
performance in the market and also covers it’s financial losses. So, these
companies are merged in well-established company to meet out economical
and financial condition with inferior risk. For that reason, merger is a long run
process to combine two or more than two companies freely which are having
better understanding under certain condition.
In last few decades, researchers are taking inference to do research in the
field of merger concept for the development of business and analyzed the
impact and/or performance after the merger. Lubatkin (1983) addressed the
issues of merger and shows benefits related to the acquiring firm. Berger et al.
(1999) provided a comprehensive review of studies for evaluating mergers and
acquisitions (M&As) in banking industry. Maditinos et al. (2009) investigated
the short as well as long merger effects of two banks and it’s performance was
recorded from the balance sheet. Golbe and White (1988) discussed time
dependence in M&As and concluded that merger series strongly follows
autoregressive pattern. They also employed time series regression model to
observe the simultaneous relationship between mergers and exogenous
variables. Choi and Jeon (2011) applied time series econometric tools to
investigate the dynamic impact of aggregate merger activity in US economy
and found that macroeconomic variables and various alternative measures
have a long-run equilibrium relationship at merger point. Rao et al. (2016)
studied the M&As in emerging markets by investigating post-M&A
performance of ASEAN companies and found that decrease in performance is
particularly significant for M&As and gave high cash reserves. Pandya (2017)
measured the trend in mergers and acquisitions activity in manufacturing and
non-manufacturing sector of India with the help of time series analysis and
recorded the impact of merger by changes with government policies and
political factors.
The above literatures have discussion on economical and financial point of
view whereas merged series can be explored to know the dependence on time
as well as own past observations. So, merger concept may be analyzed to
model the series because merger of firms or companies are very specific due
to failure of a firm or company. This existing literature argued that merger is
effective for economy both positively and negatively as per limitations.
Therefore, a time series model is developed to model the merger process and
show the appropriateness and effectiveness of the methodology in present
scenario. We have studied an autoregressive model to construct a new time
series model which accommodate the merger/acquire of series. First proposed
the estimation methods in both classical and Bayesian framework then, tested

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