5
competitive intensity for coal blocks offered by Government
of India. The following section on data and descriptive
analysis will present more details. For coal blocks auction
from 2014 to 2023, on an average 4 bidders participated
as we find by analyzing data for this study. The coal blocks
that were put up for auction had their public information
available for free download from the auction website. The
freely available information typically included topological
maps, summary information on geological features, min-
ing technology applicable, peak rated capacities, distribu-
tion of land ownership (surface rights), location of logistics
facilities, project affected people, and such others (MSTC,
2023). These pieces of information may help potential bid-
ders to consider bidding. Detailed dossiers that included
geological reports, mining plans, other investigation
reports, and land-use reports were available for purchase on
payment of low fees (Tongia &Sahgal, 2019).
Bidders bid for coal blocks on the basis of money value
they were willing to pay to the government of India (or to
the state in which the coal blocks were located) for every
tonne of coal extraction or in some cases as percentage of
revenue share they were willing to share with government
(Jain, 2022). From the studies cited in the literature review,
the theoretical background for dependence of these bid
amounts on common value of coal blocks and competitive
intensity is proposed to be examined in this paper.
The observations of auction results indicated that many
of the bids were more than the market value of equivalent
quality of coal available in the market from CIL (Dipu,
2022). These were also considered more than the profit
potential from those coal blocks considering the estimated
costs of mining and revenues from sale of coal at CIL prices
(PwC, 2015). This surplus of bid amount for a coal block
above the CIL price of equivalent quality of coal is defined
for this paper as Excess Bid, and we study its relationship of
variables of our interest.
From the results of the coal block auctions, we ask the
following questions:
a. Does the public information value of coal block
impact the bid amount for the offered coalmine?
Does the public information value of coal block
impact the Excess Bid for the offered coalmine?
b. Does competitive intensity impact the bid amount
for the offered coalmine? Does competitive intensity
impact the Excess Bid for the offered coalmine?
c. Are their moderation or mediation effects of com-
petitive intensity on the relationship between public
information value and bid amount or Excess Bid?
The theoretical grounding and consequent hypotheses are
presented in the following sections of our paper. These sec-
tions will define the models used, moderation and media-
tion effects, and variables used, including those to construct
the public information value scale. In this section of the
paper, we present the motivation for our research.
The answer to these questions can provide insights into
key parameters that influence outcomes of bidding process
in common value auction. They can indicate if the public
information is enough for attracting higher competition or
if the competitive intensity is driven by private information
values. These can provide further insight into the behavior
of the bidders as well as how to best structure incentives
for bidding in order to maximize efficiency of auction pro-
cess for mineral assets. These insights are our contribution
to the literature and to the management of auction pro-
cesses for mineral assets that governments faced with high
demand for such assets may use.
LITERATURE REVIEW
Auctions are described as Bayesian Games with Incomplete
Information in economics literature (Gibbons, 1997). These
games have public component of information that is avail-
able to all participants. There is also an Acknowledgment
of value of the subject of bidding game but that value if
unknown to participants who have their own estimates of
value based on private information that they individually
have (Gibbons, 1997). The extant literature on such games
explore existence of equilibria, optimal strategies, maxi-
mizing revenue, and approximating equilibria in complex
sequential auctions. The research provides insights into
how private information and Bayesian reasoning shape bid-
ding behavior and market outcomes.
Several papers explore auctions as Bayesian games
where bidders have private information unknown to oth-
ers. Amann &Leininger (1996) proves the existence of
equilibria in asymmetric all-pay auctions, focusing on first-
price auctions. Jackson &Swinkels (1999) shows incen-
tive-compatible sharing rules can induce equilibrium in
discontinuous games like auctions. Tang, Wang &Zhang
(2016) finds optimal bidding strategies in first-price and
all-pay auctions. Leaders bid passively to threaten followers
and gain higher payoffs. Jamal &Sunder (1996) simulates
three asset markets where traders have imperfect informa-
tion and finds they converge to the same Bayesian equilib-
rium, showing market rationality emerges from structure,
not individuals (Becker 1962 Simon 1976). Crémer &
McLean (1988) shows sellers can use bidders’ private infor-
mation to maximize revenue in Bayesian and dominant-
strategy auctions by constructing appropriate lotteries.
competitive intensity for coal blocks offered by Government
of India. The following section on data and descriptive
analysis will present more details. For coal blocks auction
from 2014 to 2023, on an average 4 bidders participated
as we find by analyzing data for this study. The coal blocks
that were put up for auction had their public information
available for free download from the auction website. The
freely available information typically included topological
maps, summary information on geological features, min-
ing technology applicable, peak rated capacities, distribu-
tion of land ownership (surface rights), location of logistics
facilities, project affected people, and such others (MSTC,
2023). These pieces of information may help potential bid-
ders to consider bidding. Detailed dossiers that included
geological reports, mining plans, other investigation
reports, and land-use reports were available for purchase on
payment of low fees (Tongia &Sahgal, 2019).
Bidders bid for coal blocks on the basis of money value
they were willing to pay to the government of India (or to
the state in which the coal blocks were located) for every
tonne of coal extraction or in some cases as percentage of
revenue share they were willing to share with government
(Jain, 2022). From the studies cited in the literature review,
the theoretical background for dependence of these bid
amounts on common value of coal blocks and competitive
intensity is proposed to be examined in this paper.
The observations of auction results indicated that many
of the bids were more than the market value of equivalent
quality of coal available in the market from CIL (Dipu,
2022). These were also considered more than the profit
potential from those coal blocks considering the estimated
costs of mining and revenues from sale of coal at CIL prices
(PwC, 2015). This surplus of bid amount for a coal block
above the CIL price of equivalent quality of coal is defined
for this paper as Excess Bid, and we study its relationship of
variables of our interest.
From the results of the coal block auctions, we ask the
following questions:
a. Does the public information value of coal block
impact the bid amount for the offered coalmine?
Does the public information value of coal block
impact the Excess Bid for the offered coalmine?
b. Does competitive intensity impact the bid amount
for the offered coalmine? Does competitive intensity
impact the Excess Bid for the offered coalmine?
c. Are their moderation or mediation effects of com-
petitive intensity on the relationship between public
information value and bid amount or Excess Bid?
The theoretical grounding and consequent hypotheses are
presented in the following sections of our paper. These sec-
tions will define the models used, moderation and media-
tion effects, and variables used, including those to construct
the public information value scale. In this section of the
paper, we present the motivation for our research.
The answer to these questions can provide insights into
key parameters that influence outcomes of bidding process
in common value auction. They can indicate if the public
information is enough for attracting higher competition or
if the competitive intensity is driven by private information
values. These can provide further insight into the behavior
of the bidders as well as how to best structure incentives
for bidding in order to maximize efficiency of auction pro-
cess for mineral assets. These insights are our contribution
to the literature and to the management of auction pro-
cesses for mineral assets that governments faced with high
demand for such assets may use.
LITERATURE REVIEW
Auctions are described as Bayesian Games with Incomplete
Information in economics literature (Gibbons, 1997). These
games have public component of information that is avail-
able to all participants. There is also an Acknowledgment
of value of the subject of bidding game but that value if
unknown to participants who have their own estimates of
value based on private information that they individually
have (Gibbons, 1997). The extant literature on such games
explore existence of equilibria, optimal strategies, maxi-
mizing revenue, and approximating equilibria in complex
sequential auctions. The research provides insights into
how private information and Bayesian reasoning shape bid-
ding behavior and market outcomes.
Several papers explore auctions as Bayesian games
where bidders have private information unknown to oth-
ers. Amann &Leininger (1996) proves the existence of
equilibria in asymmetric all-pay auctions, focusing on first-
price auctions. Jackson &Swinkels (1999) shows incen-
tive-compatible sharing rules can induce equilibrium in
discontinuous games like auctions. Tang, Wang &Zhang
(2016) finds optimal bidding strategies in first-price and
all-pay auctions. Leaders bid passively to threaten followers
and gain higher payoffs. Jamal &Sunder (1996) simulates
three asset markets where traders have imperfect informa-
tion and finds they converge to the same Bayesian equilib-
rium, showing market rationality emerges from structure,
not individuals (Becker 1962 Simon 1976). Crémer &
McLean (1988) shows sellers can use bidders’ private infor-
mation to maximize revenue in Bayesian and dominant-
strategy auctions by constructing appropriate lotteries.