URP 4273 : U RBAN G OVERNANCE
Md. Manjur Morshed, Assistant Professor Department of Urban and Regional Planning
Khulna University of Engineering and Technology
L ECTURE 2
P REVIOUS C LASS
Cold War:
Western Bloc (the United States, its NATO allies and others) and powers in the Eastern Bloc (the Soviet Union and its allies in the Warsaw Pact)
1947–1991: No large-scale fighting directly
Wars: Korea, Vietnam (1955-75) and Afghanistan (1979-1989)
Fall of Berlin Wall: 1989
End of Cold War, 1991
Backdrop of military dictatorship:
http://en.wikipedia.org/wiki/Military_dictatorship
R ISE OF ‘G OVERNANCE ’
From the mid-1970s: neo-liberalism as the orthodoxy
Economic policies of the IMF, the World Bank and WTO
Focus upon governance, rather than government per se
Existing political system could not respond to the needs of all social groups
Private sector is for-profit
Accountability of public and private sector:
Sub-contracting delivery of public services
Market mechanisms into relatively non-marketised
Relationships between the state and ‘civil society’
A collective benefit cannot be achieved by either acting separately
Governments and organised business have common interest
Civil society becomes the primary locus for the expansion of democratic and civil rights.
S TRUCTURE OF G OVERNANCE
S TRUCTURE OF G OVERNANCE
No grassroots democracy – a political government
Private sector is at the ‘robber-baron’ phase of maturation
Integrity or capacity of ‘civil society’ is questionable
NGOs (non-profit) has served the poor well
NGOs are an entry point to the civil society
About 15% of total overseas development aid is through NGOs
NGO S AND G OVERNANCE
NGOs:
non-government and non-profit organisations
Comprised of volunteers and concerned with distinct policy objectives
Typical NGOs:
Charities,
interest groups (political agendas and objectives)
Social movements, neighbourhood organisations and other civil associations
NGO problematic:
Common and conflicting views and interests
NGOs are often ideological in their positions
e.g. public interest and environmental NGOs
‘Civil society’ or ‘the politics of right-bearing bourgeois citizens’
NGO P ROBLEMATIC – C ASE S TUDY
NGO P ROBLEMATIC – C ASE S TUDY
Failure of Governance: Most powerful groups promote their interests
C ASE S TUDY :
R EADING M ATERIAL -J OURNAL
How do the illegal land development operate?
How is the illegal land price determined?
B ACKGROUND
Illegality is the only option for the majority
Inhabitants take responsibility into their own hands
Illegal subdivisions are cheaper than formal (or govt.)
Formalization of illegal subdivisions is a lengthy & costly process
S TUDY A REA
T HEORY : H EDONIC P RICING
Land price in developing countries mainly depends on institutional factors, e.g.:
Formal or informal/illegal
What other factors?
Under ideal conditions, equation 2 can explain the relative contributions of the attributes determining the land price:
Land Price = α + β1 FORMAL + ∑bi*Mi + ∑cj*Xj + ei …….……...(2)
Here,
α = constant;
β1 FORMAL= binary variable (formal or informal/illegal);
bi= relative contribution of macro-factors (locational attributes);
Mi= macro-locational characteristics;
cj= relative contribution of micro-factors (structural attributes);
Xj= independent micro-variable (residential or commercial, distance from parks etc.);
ei= standard error
T HEORY : H EDONIC A DJUSTMENT
S TUDY A REA
T HEORY : H EDONIC A DJUSTMENT
Land price = α+ β1(IDMDP) + β2(ODMDP) + β3DPNT + β4DAIRP + β5DCOMMC + β6DGHIGHW + β7DPR + β8RLAND
+ β9COMLAND+ β10PRSZ + β11REPG +β12REPM +ei………..(3)
Here, α – constant ; β1, β2…β12 – relative contribution of the independent variables; IDMDP– inside or not the metropolitan area (binary variable); ODMDP – outside or not the metropolitan area (binary variable); DPNT – distance from the new town; DAIR– distance from the Airport; DCOMMC– distance from the commercial centre;
DGHIGHW – distance from the nearest government highway; DPR– distance from the nearby proposed government road; RLAND– residential (binary variable); COMLAND– commercial land (binary variable); PRSZ– project size;
REPG– reputation of the company (good or not) (binary variable);REPM– reputation of the company (medium or not) (binary variable); ei– standard error;
A NALYSIS : F ACTOR OF R EPUTATION
Name Previous
Track
Acquire Land (>10%)
Proposed Area
Land Delivery
Permission Design Influence Score Reputation
Lotus Valley √ 1 Bad
Pixel City √ √ √ 3 Med
Eastwood City √ √ √ √ √ √ 6 Good
Roseland City √ 1 Bad
Gold Man City √ √ 2 Bad
Purbachal HL √ √ √ 3 Med
Greenland Town √ √ 2 Bad
Vision 21 Purbachal City √ √ √ 3 Med
Platinum Purbchal City √ √ √ 3 Med
Ashalaya √ √ √ √ √ √ √ 7 Good
Dhaka Village √ √ √ √ √ √ √ 7 Good
Ananda City √ √ √ 3 Med
Shikhder Royal City √ √ √ 3 Med
Bishwas Purbachal Hill City √ √ √ 3 Med
Purbachal Marinen City √ √ 2 Med
Purbachal American City √ √ √ √ √ 5 Good
East American City √ √ √ √ √ √ 6 Good
Nobodoy Housing √ √ √ 3 Med
Bestway √ √ √ √ √ √ 6 Good
Probashi Palli-1 √ √ √ 3 Med
Purbachal Regent Town √ √ √ 3 Med
Purbachal Park Town √ √ 2 Bad
Eastern Japan City √ 1 Bad
Eastern Park City √ 1 Bad
Ashian Shitol Saya √ √ √ √ √ √ √ 7 Good
NRB Homes √ √ √ √ √ √ 6 Good
Vision Park View City √ √ √ 3 Med
Regent River View √ 1 Bad
*Bad ≤ 2; Medium > 2 < 4; Good ≥ 4
A NALYSIS : D ESCRIPTIVE S TATISTICS
Variables N Minimum Maximum Mean Std. Deviation
Land Price 56 3.50 21.70 11.04 3.59
IDMDP 14
ODMDP 14
DPNT* 28 0 12.00 3.89 3.95
DAIR* 28 13.66 28.50 19.94 4.01
DCOMMC* 28 12.56 24.70 17.72 3.60
DGHIGHW* 28 0 11.75 0.92 2.33
DPR* 28 0 4.68 0.93 1.31
RLAND** 28 3.5 16 9.54 3.07
COMLAND** 28 5.5 21.7 13.02 3.93
PRSZ*** 28 203 2998 806.87 614.15
REPG 8
REPM 12
A NALYSIS : L INEAR R EGRESSION
Model Unstandardized Coefficient
t Sig.
B Std. Error
Constant 22.246 4.719 4.714 .000
IDMDP/ODMDP -1.909 1.224 -1.559 .123
DNT -.187 .178 -1.054 .295
DAIR -.525 .209 -2.519 .014
DCOMMC -.082 .098 -.835 .406
DGHIGHW -.192 .163 -1.182 .241
DPRD .934 .319 2.925 .005
RLAND -1.445 .665 -2.174 .033
COMLAND 2.019 .667 3.027 .003
RPRSZ .001 .001 .712 .478
REPG 3.277 1.101 2.977 .004
REPM .446 .828 .538 .592
A NALYSIS : L INEAR R EGRESSION
Land Price: 11.47 - 0.37X1 + 2.03X2 + 2.82X3 - 1.45X4
(R Squared = 0.51)
Here, X1= Distance from the new town;
X2= Land Character (commercial plot);
X3= Reputation of the Company (good or not);
X4= Land Character (resident plot)
L IMITATIONS
Hedonic assumption is heavily dependent on locational factors
But, price can mostly be attributed to the micro-locational factors e.g. distance from the new town.
Secondly, land price is highly co-related with the reputation of the developers.
Reputation of the developers is determined by political and
economic influence of the owners – this however difficult to justify quantitatively.
The field survey suggests that present land market is a virtual one, and the proposed area of the land developers often overlap and/or less than the proposed area. Therefore, actual locations of these developers can vary significantly from what the land developers show in their maps.
C ONCLUSION
Rather than the major hedonic assumptions of the subdivision price, distance from the government project, land character –
commercial land or connectivity based sprawl type development and good reputation of the land developer company determines the land price.
Informal market is a dynamic one – hard to define the factors
Governance is, similarly, dynamic – difficult to provide a strict framework.
C ONCLUSION
Rather than the major hedonic assumptions of the subdivision price, distance from the government project, land character –
commercial land or connectivity based sprawl type development and good reputation of the land developer company determines the land price.
Informal market is a dynamic one – hard to define the factors
Governance is, similarly, dynamic – difficult to provide a strict framework.
Thank You
