Natural Hazards and Regional Economic Growth

Transcription

1 Institute of Public Finance, University of Innsbruck alps-centre for Natural Hazard Management supported by DRAFT August 17, 2006

2 Agenda 1 Situation 2 Literature overview Theortical model 3 Data Results 4

3 Background Situation Natural Hazards=f(Natural Process, Human behaviour) Human "economic" behaviour determined by institutional framework

4 Background Situation Natural Hazards=f(Natural Process, Human behaviour) Human "economic" behaviour determined by institutional framework Analysis of "societal exposure" or "institutional resilience"

5 Background Situation Natural Hazards=f(Natural Process, Human behaviour) Human "economic" behaviour determined by institutional framework Analysis of "societal exposure" or "institutional resilience"

6 Objective Situation "Institutions matter" in Natural Hazard Management Provision of a theoretical and empirical framework

7 Objective Situation "Institutions matter" in Natural Hazard Management Provision of a theoretical and empirical framework Application to economic growth:

8 Objective Situation "Institutions matter" in Natural Hazard Management Provision of a theoretical and empirical framework Application to economic growth: 1 Regional level (NUTSII) - spatial boundaries 2 Dynamic panel data - time effects 3 Institutional variable: risk transfer mechanism

9 Objective Situation "Institutions matter" in Natural Hazard Management Provision of a theoretical and empirical framework Application to economic growth: 1 Regional level (NUTSII) - spatial boundaries 2 Dynamic panel data - time effects 3 Institutional variable: risk transfer mechanism Empirical tool: 1 International institutional comparison 2 Evaluation 3 Forcasts

10 Objective Situation "Institutions matter" in Natural Hazard Management Provision of a theoretical and empirical framework Application to economic growth: 1 Regional level (NUTSII) - spatial boundaries 2 Dynamic panel data - time effects 3 Institutional variable: risk transfer mechanism Empirical tool: 1 International institutional comparison 2 Evaluation 3 Forcasts

11 Literature overview Theortical model Disaster and Economic Growth - Theoretical work Climate change and economic growth (Fankhauser & Tol 2005, Greiner 2005) Upper and lower level impact (Albala-Bertrand 1993) Economics of disaster management (Tol & Leek 1999) Pollution, changes in disaster probability and growth (Ikefuji & Horii 2006)

12 Literature overview Theortical model Disaster and Economic Growth - Empirical studies Capital loss and respone expenditure (Albala-Bertrand 1993) Effects on input factors (K+, L ) and total factor productivity (+) (Skidmore & Toya 2002) Disasters and institutional quality (Kahn 2005, Tavares 2004)

13 Theoretical model Literature overview Theortical model Starting point: 1 Solow growth model (Mankiw, Romer & Weil 1992) and 2 Economics of disaster management (Tol & Leek 1999) Cobb-Douglas production function at time t: Y t = Kt α (A t L t ) 1 α (1)

14 Theoretical model Literature overview Theortical model Starting point: 1 Solow growth model (Mankiw et al. 1992) and 2 Economics of disaster management (Tol & Leek 1999) Cobb-Douglas production function at time t: Y t aggregate production K t capital input A t level of technology L t labour input Y t = K α t (A t L t ) 1 α (1) 0 < α < 1

15 Theoretical model Literature overview Theortical model Starting point: 1 Solow growth model (Mankiw et al. 1992) and 2 Economics of disaster management (Tol & Leek 1999) Cobb-Douglas production function at time t: Y t aggregate production K t capital input A t level of technology L t labour input Y t = K α t (A t L t ) 1 α (1) 0 < α < 1

16 Dynamics of capital Literature overview Theortical model 1 Introducing natural hazards D in the model 2 Assumption: Number of effective labour, A t L t, grows at exogenously rate (n + g) k = sy t (n + g + δ) k t D (F t, φ t ) k t (2)

17 Dynamics of capital Literature overview Theortical model 1 Introducing natural hazards D in the model 2 Assumption: Number of effective labour, A t L t, grows at exogenously rate (n + g) k = sy t (n + g + δ) k t D (F t, φ t ) k t (2) k stock of capital per unit of labour, K/AL s constant rate of saving δ constant rate of depreciation D damage function from natural hazards F t magnitude φ t institutional resilience e.g. insured assets

18 Dynamics of capital Literature overview Theortical model 1 Introducing natural hazards D in the model 2 Assumption: Number of effective labour, A t L t, grows at exogenously rate (n + g) k = sy t (n + g + δ) k t D (F t, φ t ) k t (2) k stock of capital per unit of labour, K/AL s constant rate of saving δ constant rate of depreciation D damage function from natural hazards F t magnitude φ t institutional resilience e.g. insured assets

19 Dynamics of capital Literature overview Theortical model Effects of D on the development of k: 1 F t denotes the size damage in D t - negative 2 φ t amount of insured losses - mitigation effects on D t 3 φ t designated savings and reserves - negative

20 Data Results Econometric equation - Panel data model ln (y it ) = β it + β 1 ln (y it 1 ) + β 2 ln (s it ) +β 3 ln (n it + g + δ) + β 4 D it + µ i + η t + ɛ it (3) y it GDP per capita s it Investment per capita (n it + g + δ) population growth, technology growth and depreciation 1 D it hazard vector (hazard dummy, interaction term) µ i regional fixed effects η t time specific effects (year) ɛ it error term 1 (g + δ = 0.05)

21 Empirical strategy Data Results 1 Data overview 2 Cross-section analysis - long term effects 3 Dynamic panel estimates (System-GMM) Arellano & Bond (1991) Base estimates and flood events Effects of floods over time Effects of flood events and national risk transfer mechanisms

22 Data Data Results 20 European countries EU 15 + CZ, H, N, PL & CH NUTSII-level 202 regions Yearly data GDP - Investment European Regional Database - Population Cambridge Econometrics - Area Historical flood events EM-DAT, CRED Brussels National risk transfer Von Ungern-Sternberg (2004)

23 Data Results Effects of flood events on growth - OLS, Dependent Variable ln(y it) ln(y it 1 ) *** *** *** (0.0724) (0.0689) (0.0671) ln( s i) *** *** *** (0.0866) (0.0824) (0.0798) ln(n it + g + δ) *** *** *** P Floodi (0.2606) (0.2578) (0.2539) * ** P (0.0176) Floodi Ins i ** (0.0153) Constant Number of obs Prob>F R

24 Data Results Effects of flood events on growth - Dynamic Panel (System-GMM) Dependent Variable ln(y it ) ln(y it 1 ) *** *** *** *** *** (0.0071) (0.0072) (0.0072) (0.0068) (0.0072) ln(s it ) *** *** *** *** * (0.0076) (0.0074) (0.0076) (0.0071) (0.0076) ln (n it + g + δ) *** *** *** *** *** (0.0115) (0.0111) (0.0119) (0.0108) (0.0109) Flood it (0.0128) Flood it *** (0.0139) Flood it *** (0.0114) Flood it ** (0.0100) Year specific effects Yes Yes Yes Yes Yes Region specific effects Yes Yes Yes Yes Yes Constant Number of obs. 4,608 4,608 4,608 4,408 4,208 Prob>chi Hansen test AR(1) AR(2)

25 Data Results Effects of flood events on growth - Dynamic Panel (System-GMM) Dependent Variable ln(y it ) ln(y it 1 ) *** *** *** (0.0073) (0.0072) (0.0068) ln(s it ) *** *** *** (0.0077) (0.0076) (0.0071) ln (n it + g + δ) *** *** *** (0.0111) (0.0117) (0.0108) F it * (0.0130) F it Ins it *** (0.0169) F it ** (0.0156) F it 1 Ins it ** (0.0153) F it *** (0.0114) F it 2 Ins it ** (0.0153) Number of obs. 4,608 4,608 4,408 Prob>chi Hansen test AR(1) AR(2)

26 Discussion 1 Significant negative impact of floods on economic growth Cross-section, long term Panel-data: short and medium term 2 Mitigating effects of mandatory insurance systems 3 Effects of institutional variables on flood and investment variables 4 Limitations: No variable for costs of disaster management Risk transfer vs. Country group

27 "Institutions matter" Promising approach/tool Future research: Simulation (e.g. increase in flood frequency) Forecasts: Future costs of flood events Institutional resilience More institutional variables: Variation over time Variation between countries (regions)

28 Albala-Bertrand, J. M. (1993), Natural disaster situations and growth: A macroeconomic model for sudden disaster impacts, World Development 21(9), Arellano, M. & Bond, S. (1991), Some tests of specification for panel data: Monte carlo evidence and an application to employment equaations, Review of Economic Studies 58, Fankhauser, S. & Tol, R. S. J. (2005), On climate change and economic growth, Resource and Energy Economics 27, Greiner, A. (2005), Anthropogenic climate change and abatement in a multi-region world with endogenous growth, Ecological Economics 55(2), Ikefuji, M. & Horii, R. (2006), Natural disasters in a two-sector model of endogenous growth, mimeo, Graduate School of Economics, Osaka University.

29 Kahn, M. E. (2005), The death toll from natural disasters: The role of income, geography, and institutions, The Review of Economics and Statistics 87(2), Mankiw, G. N., Romer, D. & Weil, D. N. (1992), A contribution to the empirics of economic growth, The Quarterly Journal of Economics 107(2), Skidmore, M. & Toya, H. (2002), Do natural disasters promote long-run growth?, Economic Inquiry 40(4), Tavares, J. (2004), The open society assesses its enemies: shocks, disasters and terrorist attacks, Journal of Monetary Economics 51, Tol, R. S. J. & Leek, F. P. M. (1999), Economic analysis of natural disasters, in T. E. Downing, A. A. Olsthoorn & S. J. Tol, Richard, eds, Climate, Change and Risk, Routledge, pp

30 Von Ungern-Sternberg, T. (2004), Efficient Monopolies: The Limits of Competition in the European Property Insurance Market, Oxford University Press.