The main objective of this study is to contribute toward an analytical and empirical work on the oil-based developing economy of Iran. It focuses on the aggregate behavior of the Iranian economy through a simple linear econometric model. After a survey of the literature on the theoretical framework of macroeconomic models for the developing countries in general, and for the oil exporting developing countries in particular, a linear econometric model for the Iranian economy is formulated and its logical and economical aspects are explained. The proposed model consists of basic consumption, production, foreign trade, and employment relationships. Estimation of the behavioral equations are carried out by Ordinary Least Square and Two Stage Least Square estimators. The model is estimated over the period of 1959-76. Data published by the Plan and Budget Organization of Iran in the 1978 edition of the "Economic Trends of Iran" are used for the estimation of the parameters of the model. Historical simulation of the model has been performed to test the validity and the fitness of the model as a whole. The results obtained from the estimation of the consumption functions seem to indicate that the aggregate Iranian consumption behavior can be best explained by Friedman's Permanent Income Hypothesis. An attempt has been made to estimate the aggregate production function of the urban sector according to various Cobb-Douglas production functions and linear production function with constant returns to scale. All of these specifications gave implausible results. In general, the results of this study demonstrate that the links between different sectors of the Iranian economy are very weak and the import substitution strategy of the government during the period of study failed to establish a genuine domestic industrial base and to reduce its dependence on foreign resources.

In many real-world settings, individuals face a dynamic decision problem: choices in the present have an impact on future outcomes. It it important for researchers to recognizing these dynamic forces so that we are able to fully understand the trade-offs an individual faces and to correctly estimate the parameters of interest. I study dynamic decision making in three diverse contexts: residential choice of families in New Zealand, search strategies of ridesharing drivers in Texas, and welfare participation of single mothers in Michigan. In each of these, I motivate the analysis using a theoretical model, and bring the model to the data to estimate parameters and evaluate testable implications. In the first chapter, I ask: how do schools affect where families choose to live and does their effect contribute to residential segregation? I study these questions using unique administrative microdata from Auckland, New Zealand, an ethnically diverse -- but segregated -- city. I develop and estimate a dynamic model of residential choice where forward-looking families choose neighborhoods based on their children's schools, local amenities, and moving costs. Previous studies typically estimate school quality valuations using a boundary discontinuity design. I leverage attendance zones in this setting to also generate reduced form estimates using this methodology. The structural model estimates show that the valuation of school quality varies by the child's school level and the family's ethnicity; the reduced form approach, however, cannot capture this heterogeneity. Moreover, I find that the reduced form estimates are aligned only with white families' valuations of quality. The model estimates also show that families experience a high disutility from moving houses if it results in their child changing school. In counterfactuals, I show that residential segregation increases as the link between housing and schools weakens. In the second chapter, co-authored with Vinayak Iyer, we ask: what drives the efficiency in ridesharing markets? In decentralized transportation markets, search and match frictions lead to inefficient outcomes. Ridesharing platforms, who act as intermediaries in traditional taxi markets, improve upon the status quo along two key dimensions: surge pricing and centralized matching. We study how and why these two features make the market more efficient; and explore how alternate pricing and matching rules can improve outcomes further. To this end, we develop a structural model of the ridesharing market with four components: (1) dynamically optimizing drivers who make entry, exit and search decisions; (2) stochastic demand; (3) surge pricing rule and (4) a matching technology. Relative to our benchmark model, surge pricing generates large gains for all agents; primarily during late nights. This is driven by the role surge plays in inducing drivers to enter the market. In contrast, centralized matching reduces match frictions and increases surplus for consumers, drivers, and the ridesharing platform, irrespective of the time of the day. We then show that a simple, more flexible pricing rule can generate even larger welfare gains for all agents. Our results highlight how and why centralized matching and surge pricing are able to make the market more efficient. We conclude by drawing policy implications for improving the competitiveness between taxis and ridesharing platforms. In the third chapter, co-authored with Lucas Husted, we ask: does removing families from welfare programs result in increased employment? Using detailed administrative data from Michigan, we study a policy reform in the state's TANF program that swiftly and unexpectedly removed over 10,000 families from welfare while quasi-randomly assigning time limits to over 30,000 remaining participants. We motivate our analysis using a dynamic model of welfare benefits usage. Consistent with economic theory, removing families from welfare increases formal labor force participation by roughly 4 percentage points (20\% over control group mean), with increases in annualized earnings of roughly \$500. However, despite this, the majority of families remain formally unemployed after welfare removal, and using quantile regressions we show that even the highest percentile wage gains fail to offset the loss in welfare benefits. The policy even affects families who are far from exhausting their time-limited benefits. Under a dynamic model, families have an incentive to bank benefits for future use -- an effect we observe in the data. Overall, our findings provide evidence that, contrary to their stated goals, welfare reform measures that either kick families off welfare or make welfare harder to access could possibly deepen poverty.

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This dissertation studies how the digitalization of commercial banking affects bank competition, financial stability, and monetary policy transmission. In the first chapter, The Digital Banking Revolution: Reduced Form Evidence, I use hand-collected data and a novel identification strategy to show that after adopting digital platforms, banks branchlessly operate in more markets, and mid-size banks, those with relatively high quality digital platforms but without extensive branch networks, grow faster. Further, bank balance sheet composition tilts to uninsured deposits on the funding side, and to high income borrowers on the loan side. In the second chapter, The Digital Banking Revolution: Aggregate Effects on Competition and Stability, in order to disentangle the underlying mechanisms and quantify aggregate effects, I build a structural model of the U.S. banking system and compare the observed digital equilibrium to a counterfactual without digital platforms. The model allows for endogenous adoption of digital platforms, branch networks, market entry, and accounts for digitalization among non-banks. Digitalization decreases local and national market concentration, and average markups fall in deposit and loan markets, holding fixed the size of the banking sector. Consumers capture most of the surplus created by digitalization, however it accrues mostly to wealthier segments of the economy. As for stability, it increases the average market share of lightly-regulated mid-sized banks, increases the uninsured deposits ratio of the banking sector while re-sorting uninsured deposits towards larger digital banks, and doubles credit risks associated with lending in market segments that are less-well served by digital technologies. In sum, digital banking increases competition and poses risks to financial stability. In the third chapter, Destabilizing Digital "Bank Walks", which is co-authored with Tano Santos and Luigi Zingales, we study the impact of digital banking on the value of the deposit franchise and the transmission of monetary policy through bank balance sheets. We find that when the Fed funds rate increases, deposits flow out faster and the cost of deposits increases more in banks with a digital platform. The results are similar for insured and non-insured deposits. We find that correcting for digital betas and deposit outflows results in a deposit franchise value that is significantly lower for digital-broker banks relative to a traditional bank without digital platform. We apply this analysis to Silicon Valley Bank (SVB) and find that the reduced value of the deposit franchise explains why SVB was insolvent in early March 2023, even before the bank run occurred.

Using 1980 - 2012 annual data, the study empirically investigates the dynamic relationship between financial development and economic growth in three developing countries (South Africa, Brazil and Kenya) and three developed countries (United States of America, United Kingdom and Australia). The study was motivated by the current debate regarding the role of financial development in the economic growth process, and their causal relationship. The debate centres on whether financial development impacts positively or negatively on economic growth and whether it Granger-causes economic growth or vice versa. To this end, two models have been used. In Model 1 the impact of bank- and market-based financial development on economic growth is examined, while in Model 2 it is the causality between the two that is explored. Using the autoregressive distributed lag (ARDL) bounds testing approach to cointegration and error-correction based causality test, the results were found to differ from country to country and over time. These results were also found to be sensitive to the financial development proxy used. Based on Model 1, the study found that the impact of bank-based financial development on economic growth is positive in South Africa and the USA, but negative in the U.K – and neither positive nor negative in Kenya. Elsewhere the results were inconclusive. Market-based financial development was found to impact positively in Kenya, USA and the UK but not in the remaining countries. Based on Model 2, the study found that bank-based financial development Granger-causes economic growth in the UK, while in Brazil they Granger-cause each other. However, in South Africa, Kenya and USA no causal relationship was found. In Australia the results were inconclusive. The study also found that in the short run, market-based financial development Granger-causes economic growth in the USA but that in South Africa and Brazil, the reverse applies. On the other hand bidirectional causality was found to prevail in Kenya in the same period. / Economics / DCOM (Economics)

Using 1980 - 2012 annual data, the study empirically investigates the dynamic relationship between financial development and economic growth in three developing countries (South Africa, Brazil and Kenya) and three developed countries (United States of America, United Kingdom and Australia). The study was motivated by the current debate regarding the role of financial development in the economic growth process, and their causal relationship. The debate centres on whether financial development impacts positively or negatively on economic growth and whether it Granger-causes economic growth or vice versa. To this end, two models have been used. In Model 1 the impact of bank- and market-based financial development on economic growth is examined, while in Model 2 it is the causality between the two that is explored. Using the autoregressive distributed lag (ARDL) bounds testing approach to cointegration and error-correction based causality test, the results were found to differ from country to country and over time. These results were also found to be sensitive to the financial development proxy used. Based on Model 1, the study found that the impact of bank-based financial development on economic growth is positive in South Africa and the USA, but negative in the U.K – and neither positive nor negative in Kenya. Elsewhere the results were inconclusive. Market-based financial development was found to impact positively in Kenya, USA and the UK but not in the remaining countries. Based on Model 2, the study found that bank-based financial development Granger-causes economic growth in the UK, while in Brazil they Granger-cause each other. However, in South Africa, Kenya and USA no causal relationship was found. In Australia the results were inconclusive. The study also found that in the short run, market-based financial development Granger-causes economic growth in the USA but that in South Africa and Brazil, the reverse applies. On the other hand bidirectional causality was found to prevail in Kenya in the same period. / Economics / D. Com. (Economics)

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The maturity transformation of deposits is a primary driver of economic growth, as loans enable borrowers to spend funds, thereby growing the economy. However, if borrowers cannot repay their loans, the asset quality of banks deteriorate, resulting in non-performing loans or, worse, an economic crisis. An understanding of how macroeconomic and microeconomic determinants impact bank asset quality in South Africa can contribute to knowledge of the bank asset quality phenomenon in the African context. Due to the 2008/2009 global financial crisis, the introduction of new legislation and the value of gold exports, the South African economy presents an opportunity to make an original contribution to the knowledge of determinants that influence bank asset quality. In addition to studying bank asset quality determinants that are contested in research, this study also aims to determine whether a superior returns determinant of non-performing loans exists when comparing a bank’s profitability determinants, namely return on assets, return on equity and interest income on loans. This study applied panel data regression analysis, making use of a balanced panel approach, to study the determinants of bank asset quality. This approach recontextualises the existing bank asset quality theory for the South African financial sector. The results indicate that South Africa is not resilient against the impact of global financial crises trickling through international trade linkages and that regulatory changes do not instantly improve bank asset quality, and may even reduce the short-term asset quality. Moreover, bank asset quality in South Africa is sensitive to the total value of gold exports. It is evident from the profitability measures that the interest income on loans is the most suitable profitability measure of bank asset quality. This study provides an original contribution to bank asset quality determinants and recommends that regulators should pre-emptively determine the impact of new legislation on bank asset quality. Furthermore, interest income on loans as a profitability measure provides the most accurate results. Lastly, a single-country bank asset quality analysis is important, especially for economies that have commodity exports that significantly weigh in on the bank asset mix. / Die termyntransformasie rakende deposito's is die primêre dryfkrag vir groei in die ekonomie: Lenings maak dit vir leners moontlik om fondse te bestee, wat die ekonomie laat groei. Indien hierdie leners hul lenings egter nie kan terugbetaal nie, gaan die gehalte van bankbates agteruit, wat tot wanpresterende lenings of, nog erger, tot 'n ekonomiese krisis kan lei. As begryp kan word hoe makro-ekonomiese en mikro-ekonomiese bepalende faktore op die gehalte van bankbates in Suid-Afrika inwerk, kan dit bydra tot kennis van die verskynsel van bankbategehalte in die Afrika-konteks. In die lig van die 2008/2009 wêreldwye finansiële krisis, die uitvaardiging van nuwe wetgewing en die waarde van gouduitvoere bied die Suid-Afrikaanse ekonomie ’n geleentheid om ’n oorspronklike bydrae te lewer tot kennis van die bepalende faktore wat bankbategehalte beïnvloed. Benewens die bestudering van die bepalende faktore van die gehalte van bankbates wat in navorsing redelik omstrede is, het hierdie studie ten doel om, wanneer 'n bank se winsgewendheidsbepalers, naamlik opbrengs op bates, opbrengs op ekwiteit (eiekapitaal) en rente-inkomste op lenings, met mekaar vergelyk word, vas te stel of daar ’n superieure opbrengsbepaler van wanpresterende lenings bestaan. Vir hierdie studie is ’n regressieontleding van paneeldata uitgevoer, en daar is van ’n gebalanseerde paneelbenadering gebruik gemaak om die bepalende faktore van bankbategehalte te bestudeer. Hierdie benadering herkontekstualiseer die bestaande bankbategehalteteorie vir die Suid-Afrikaanse finansiële sektor. Die resultate van die studie dui daarop dat Suid-Afrika nie veerkragtig is om die uitwerking van wêreldwye finansiële krisisse teen te werk wat met internasionale handelskakelings deursyfer nie en dat reguleringsveranderinge nie dadelik die bankbategehalte verbeter nie; dit kan inteendeel die korttermynbategehalte verlaag. Bowendien is die bankbategehalte in Suid-Afrika gevoelig vir die totale waarde van gouduitvoere. Dit blyk uit die winsgewendheidsmaatstawwe dat die rente-inkomste op lenings die mees geskikte winsgewendheidsmaatstaf van bankbategehalte is. Hierdie studie lewer ’n oorspronklike bydrae tot die bepalers van bankbategehalte en beveel aan dat reguleerders vooruit reeds die uitwerking van nuwe wetgewing op bankbategehalte moet bepaal. Daarby voorsien rente-inkomste op lenings as winsgewendheidsmaatstaf die akkuraatste resultate. Laastens is ’n ontleding van ’n enkele land se bankbategehalte van belang, in die besonder vir ekonomieë met kommoditeitsuitvoere wat beduidend tot die samestelling van bankbates bydra. / Kadimo ya nako ye kopana ya ditipositi ke mokgwa wo bohlokwa wa kgolo ya ekonomi, ka ge dikadimo di dumelela baadimi go šomiša matlotlo, go realo e le go godiša ekonomi. Efela, ge baadimi ba sa kgone go lefela dikadimo tša bona, boleng bja thoto ya dipanka bo a phuhlama, go feleletša go e ba le dikadimo tše di sa šomego gabotse goba, go feta fao, phuhlamo ya ekonomi. Kwešišo ya ka fao ditaetšo tša makroekonomi le maekroekonomi di huetšago boleng bja thoto ya panka ka Afrika Borwa e ka ba le seabe go tsebo ya taba ya boleng bja thoto ya panka go ya ka seemo sa Afrika. Ka lebaka la mathata a ditšhelete a lefase a 2008/2009, tsebišo ya molao wo moswa le boleng bja dithomelontle tša gauta, ekonomi ya Afrika Borwa e fa sebaka seabe sa mathomo tsebong ya ditaetšo tšeo di huetšago boleng bja thoto ya panka. Go tlaleletša nyakišišong ya ditaetšo tša boleng bja thoto ya panka tšeo di ganetšwago nyakišišong, maikemišetšo a nyakišišo ye gape ke go laetša ge eba taetšo ya letseno le legolo la dikadimo tše di sa šomego gabotse di gona ge go bapetšwa ditaetšo tša poelo ya panka, e lego letseno la dithoto, letseno la dišere le letseno la dikadimo. Nyakišišo ye e šomišitše tshekatsheko ya poelomorago ya datha ya phanele, ya go šomiša mokgwa wa phanele wo o lekaneditšwego, go nyakišiša ditaetšo tša boleng bja thoto ya panka. Mokgwa wa go tšwetšapele gape teori ya boleng bja thoto ya panka ya lekala la Afrika Borwa la ditšhelete. Dipoelo di laetša gore Afrika Borwa ga e fokole kgahlanong le khuetšo ya mathata a ditšhelete a lefase ao a rothelago ka dikamanong tša kgwebišano ya boditšhabatšhaba le gore diphetogo tša taolo ga di kaonafatše boleng bja thoto ya panka ka lebelo, gomme di ka fokotša le boleng bja thoto bja paka ye kopana. Go feta fao, boleng bja thoto ya panka ka Afrika Borwa bo ela hloko boleng bja palomoka bja dithomelontle tša gauta. Go a bonagala go tšwa go dikgato tša tiro ya poelo gore letseno la tswala godimo ga dikadimo ke kgato ya poelo ye maleba gagolo ya boleng bja thoto ya panka. Nyakišišo ye e fa seabe sa mathomo ditaetšo tša boleng bja thoto ya panka gomme e šišinya gore balaodi ba swanela go laetša e sa le ka pela khuetšo ya molao wo moswa ka ga boleng bja thoto ya panka. Go feta fao, letseno la tswala godimo ga dikadimo bjalo ka kelo ya tiro ya poelo le go fa dipoelo tše di lebanego gabotse. Sa mafelelo, tshekatsheko ya boleng bja thoto ya panka ya naga e tee, kudu diekonomi tšeo di nago le dithomelontle tša ditšweletšwa tšeo gagolo di dumelelago motswako wa thoto ya panka. / Business Management / Ph. D. (Management Studies)

This study provides evidence of the relationship between bank-granted credit and business cycles in South Africa. The study is conducted in three phases, namely qualitative research (Phase I), quantitative research (Phase II) and econometric analysis (Phase III). A sequential (connected data) mixed methodology (Phase I and II) is used to collect and analyze primary data from market participants. The qualitative research (Phase I) involves structured interviews with influential or well informed people on the subject matter. Phase I of the study is used to understand the key determinants of bank credit in South Africa and to appreciate how each of the credit aggregates behaves during alternate business cycles. Qualitative survey results suggest key determinants of commercial bank credit in South Africa as economic growth, collateral value, bank competition, money supply, deposit liabilities, capital requirements, bank lending rates and inflation. The qualitative results are used to formulate questions of the structured survey questionnaire (Quantitative research- Phase II). The ANOVA and Pearman’s product correlation analysis techniques are used to assess relationship between variables. The quantitative results show that there is direct and positive relationship between bank lending behavior and credit aggregates namely economic growth, collateral value, bank competition and money supply. On the other hand, the results show that there is a negative relationship between credit growth and bank capital and lending rates. Overall, the quantitative findings show that bank lending in South Africa is procyclical. The survey results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. The econometric methodology is used to augment results of the survey study. Phase III of the study re-examines econometric relationship between bank lending and business cycles. The study employs cointegration and vector error correction model (VECM) techniques in order to test for existence of long-run relationship between the selected variables. Granger causality test technique is applied to the variables of interest to test for direction of causation between variables. The study uses quarterly data for the period of 1980:Q1 to 2013:Q4. Business cycles are determined and measured by Gross Domestic Product at market prices while bank-granted credit is proxied by credit extension to the private sector. The econometric test results show that there is a significant long-run relationship between economic growth and bank credit extension. The Granger causality test provides evidence of unidirectional causal relationship with direction from economic growth to credit extension for South Africa. The study results indicate that the case for demand-following hypothesis is stronger than supply-leading hypothesis in South Africa. Economic growth spurs credit market development in South Africa. Overall, the results show that there is a stable long-run relationship between macroeconomic business cycles and real credit growth in South Africa. The results show that economic growth significantly causes and stimulates bank credit. The study, therefore, recommends that South Africa needs to give policy priority to promotion and development of the real sector of the economy to propel and accelerate credit extension. Economic growth is considered as the significant policy variable to stimulate credit extension. The findings therefore hold important implications for both theory and policy. / Business Management / D.B.L.

Following the debate by empirical finance research on the presence of non-linear predictability in stock market returns, this study examines forecasting abilities of nonlinear STAR-type models. A non-linear model methodology is applied to daily returns of FTSE, S&P, DAX and Nikkei indices. The research is then extended to long-horizon forecastability of the four series including monthly returns and a buy-and-sell strategy for a three, six and twelve month holding period using non-linear error-correction framework. The recursive out-of-sample forecast is performed using the present value model equilibrium methodology, whereby stock returns are forecasted using macroeconomic variables, in particular the dividend yield and price-earnings ratio. The forecasting exercise revealed the presence of non-linear predictability for all data periods considered, and confirmed an improvement of predictability for long-horizon data. Finally, the present value model approach is applied to the housing market, whereby the house price returns are forecasted using a price-earnings ratio as a measure of fundamental levels of prices. Findings revealed that the UK housing market appears to be characterised with asymmetric non-linear dynamics, and a clear preference for the asymmetric ESTAR model in terms of forecasting accuracy.