bashina presentation sugar

Efficiency of simple homogeneous goods

procurement under rigid governmental

regulation: the case of sugar sand

procurement in Russia

A. Yakovlev, A. Bashina, O. Demidova

6th IPPC, Dublin

14th August

6th IPPC, Dublin, 14th August

Motivation

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Wide spread of e-auctions as a public procurement procedure

(since 2011 e-auctions are one of the most popular procurement

practices). But are they efficient or not?

Previous research shows that different procedures can give

different results for simple and complex procurements (Jean

Tirole “The Theory of Industrial Organization”, 1988).

The goal of our research:

To estimate price efficiency of different procurement procedures

using data for sugar sand procurement as an example of simple

homogeneous good.


Procurement System in Russia

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No qualification requirements, only quality of proposal

(mostly minimum price)

Formal and unified approach to procurement

procedures

Three types of procurement procedures

Unified procurement information on a common official

site http://www.zakupki.gov.ru

http://www.zakupki.gov.ru/










Empirical Research

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Auction vs negotiation: Vellez (2011), Lalive and Schmutzler

(2011), Bajari, McMillan, Tadelis (2009)

Efficiency comparing to private sector: MacDonald, Handy, Plato

(2002)

E-auctions: Soudry (2004), Singer, Roubik, Beffermann (2009),

Pavel and Sičáková-Beblavá (2013), Vaidya, Sajeev and Callender

(2006)

Political risks: Moszoro and Spiller (2012), Chong, Staropoli and

Yvrande-Billon (2009)

Corruption and collusion: Li and Zheng (2009), Chever and Moore

(2012), Porter and Zona (1993, 1997),

Procurement researches in Russia: Yakovlev, Demidova, Balaeva

(2012), Podkolzina and Morozov (2012), Balsevich, Pivovarova

and Podkolzina (2012)


Sugar market in Russia

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Strong seasonal pattern in production and

consumption

The average retail mark-up on wholesale prices is 25–

30%

Significant regional diversity in prices (till 60%)

High market concentration

Main consumers are retail consumers (approx. 50%)

and the food industry (about 40%)

Market share of public procurement is 0.5%


Data

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Data from Unified Register of State and Municipal Contracts

Simple public procurement contracts in the period from the

January 1, 2011 till the December 31, 2011

2720 contracts

All prices are divided by the average retail sugar price in Russia

Procurement market is not homogenous in terms of contract size

and prices

The most popular procurement method is request of quotation

Procurement contracts from single source are rare but give 50%

of value of all contracts in the sample

Procurement prices are 10% lower than retail prices

Use in our models only contracts with value lower than 500 000

rubles excluding contracts from the single source (2609

contracts)


Data

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Contract

value

Number

of

contracts

Share of

contracts

Average

standardised

contract price

of one kilo of

sugar

Average

standardised

starting

(maximum)

contract price of

one kilo of

sugar

Average

decrease of

the

standardised

price

Average

difference of

the contract

price from

standardised

average

regional price

Up to RUR

100,000 2229 81.95 0.900 1.015 0.102 0.076

From RUR

100,000 to

500,000

404 14.85 0.903 1.024 0.112 0.108

RUR

500,000 and

more

87 3.20 0.993 1.038 0.089 0.012

Total 2720 100 0.903 1.017 0.101 0.079


Hypotheses

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Hypothesis 1. Placement of contracts through valid e-

auctions results in a lower prices as compared to

other procurement methods.

Hypothesis 2. For larger contracts, prices are lower.

Hypothesis 3. For contracts with longer terms of

execution, prices are higher than for short-term

contracts.

Hypothesis 4. More competition leads to more

effective procurement.


Models

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Dependent variables:

the contract price for one kilogram of sugar,

decrease of the price for one kilogram of sugar in the

process of the contract placement,

deviation of the contract price for one kilogram of

sugar from the average retail price in the region at the

moment of the contract placement.

OLS-estimation with robust standard errors.

),0(~ N

,

ZXY

Higher School of Economics , Moscow, 2013

Test for coefficients equality for different

procedures

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Model

Price Price decrease Price deviation

E-auction

vs. void e-

auction

E-auction vs.

request of

quotation

E-auction vs.

request of

quotation

E-auction

vs. void e-

auction

E-auction

vs. request

of

quotation

with

continuous

contract

volume

Test 11.72*** 6.60*** 20.75*** 12.77*** 6.06***

Dummy

coefficient -0.453*** 0.062*** 0.280*** 0.269** -0.067***

with dummy

variables for

contract

volume

Test 12.77*** 7.39*** 28.38*** 14.10*** 6.76***

Dummy

coefficient -0.469*** 0.051** 0.287*** 0.283** -0.057***


Models for contract price

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Regressors

(1) (2) (3) (4) (5) (6)

E-auction Void e-auction Request for

quotation E-auction Void e-auction

Request for

quotation

Contract volume (kg) -1,15e-05*** 1,60e-06 -8,11e-06***

(2,72e-06) (5,07e-06) (1,56e-06)

Number of participants -0,025*** -0,035*** -0,021* -0,037***

(0,010) (0,009) (0,012) (0,009)

Squared number of participants 0,003*** 0,003*** 0,002 0,002**

(0,001) (0,001) (0,001) (0,001)

Contract duration 2,49 e-04*** -2,82 e-04** 7,99e-05* 2,37 e-04*** -2,784 e-04** 5,63e-05

(6,39e-05) (1,197 e-04) (4,46e-05) (6,56e-05) (1,17 e-04) (4,54e-05)

Standardized average regional price 0,412*** 0,969*** 0,446*** 0,385*** 0,960*** 0,439***

(0,052) (0,143) (0,036) (0,055) (0,1382375) (0,036)

Dummies for a month yes yes yes yes yes yes

Contract value from 100 to 500 thousands

rublesc)

-0,007 0,017 -0,003

(0,020) (0,023) (0,009)

Constant 0,474*** -0,156 0,532*** 0,489*** -0,011 0,534***

(0,052) (0,137) (0,037) (0,056) (0,130) (0,038)

Number of observations 839 310 1 460 839 310 1 460

R2 0,469 0,774 0,211 0,454 0,776 0,200


Models for price decrease

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Regressors

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

E-auction Request for

quotation E-auction

Request for

quotation

Contract volume (kg) 8,58e-06*** -4,13e-06***

(2,62e-06) (1,04e-06)

Number of participants 0,052*** 0,045*** 0,049*** 0,045***

(0,007) (0,006) (0,008) (0,006)

Squared number of participants -0,003*** -0,003*** -0,003*** -2,65 e-04***

(0,001) (0,001) (0,001) (0,001)

Contract duration -1,94 e-04*** 6,74e-05** -1,86 e-04*** 6,57e-05**

(5,30e-05) (3,07e-05) (5,36e-05) (3,10e-05)

Standardized average regional price 0,227*** 0,010 0,244*** 0,013

(0,031) (0,020) (0,030) (0,020)

Dummies for month yes yes yes yes

Contract value from 100 to 500 thousands

rublesc)

0,014 -0,023***

(0,014) (0,005)

Constant -0,243*** 0,042* -0,251*** 0,035

(0,032) (0,024) (0,032) (0,025)

Number of observations 839 1 460 839 1 460

R2 0,364 0,276 0,350 0,278


Models for price deviation

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Regressors

(1) (2) (3) (4) (5) (6)

E-auction Void e-auction Request for

quotation E-auction Void e-auction

Request for

quotation

Contract volume (kg) 9,05e-06*** -1,86e-06 8,04e-06***

(2,71e-06) (5,27e-06) (1,52e-06)

Number of participants 0,022** 0,034*** 0,019* 0,036***

(0,010) (0,009) (0,011) (0,009)

Squared number of

participants

-0,002** -0,002** -0,002 -0,002**

(0,001) (0,001) (0,001) (0,001)

Contract duration -2,29 e-04*** 2,592 e-04** -7,89e-05* -2,17 e-04*** 2,565 e-04** -5,53e-05

(6,16e-05) (1,156 e-04) (4,19e-05) (6,25e-05) (1,135 e-04) (4,26e-05)

Standardized average

regional price

0,415*** 0,049 0,355*** 0,440*** 0,058 0,361***

(0,043) (0,132) (0,030) (0,045) (0,128) (0,030)

Dummies for month yes yes yes yes yes yes

Contract value from 100

000 to 500 000 rublesc)

-0,004 -0,014 0,003

(0,019) (0,023) (0,009)

Constant -0,303*** 0,001 -0,346*** -0,319*** -0,003 -0,348***

(0,044) (0,127) (0,033) (0,047) (0,121) (0,034)

Number of observations 839 310 1 460 839 310 1 460

R2 0,309 0,556 0,175 0,297 0,567 0,163


Results

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Influence of contract and procedure characteristics on the

procurement prices vary for different procurement procedures.

The placement of contracts through e-auction results in lower

prices comparing to request of quotation but not to void open

auction.

Competition matters for e-auctions an requests for quotations.

There is evidence that for larger contracts placed using e-auction

or request of quotation the sugar prices are lower .

For contracts placed by e-auction or request of quotation, there is

evidence that for contracts with longer terms of execution the

prices are higher than for short-term contracts.

Influence of the discussed factors on the prices in void e-

auctions differ from dependencies for other procurement

methods.


Policy Implication

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More precise analysis of a procurement results for void

e-auctions and procurement from a single source.

Monitoring for collusion identification.

Monitoring of large contracts especially from single

source.

Aleksandra Bashina

[email protected]

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