Gorkem Bostanci

I am an Assistant Professor of Economics at the University of British Columbia.  I study how market frictions impact aggregate productivity by distorting input allocation across firms.

Fields:  Macroeconomics, Firm Dynamics, Labor Economics, and Economics of Information 

bostanci [at] sas.upenn.edu

Labor outsourcing provides flexibility to producers but also exposes sensitive information to outsiders, which may deter outsourcing if the legal system does not provide adequate protection. I use this simple trade-off to evaluate policies that capacitate higher levels of labor outsourcing. I build an industry dynamics model where outsourcing provides flexibility to producers but might be underutilized due to a legal friction. I estimate the model using data from the U.S. states and decompose the cross-state heterogeneity in labor outsourcing into differences in firing cost, industry composition, demand volatility, and a state-level wedge. The wedge estimates correlate with trade secret protection measures across states. I find that reducing the friction for all states to match the least distorted state would increase outsourced employment by 33% and aggregate output by 0.8%. Then, using event studies around the staggered adoption of the Uniform Trade Secrets Act, I show that it led to increased outsourcing of high-skill jobs. 

Presented at UdeM, Queens U, UBC, ITAM, Bilkent U, FRBDallas, U Exeter, U Bristol, Western U, Ozyegin U, IWH, U Essex, Georgetown Qatar, Sabanci U, FRB St. Louis, SEA'21, CMSG'21, ALEA'21, SED'21, SIOE'21, EARIE'21, MMF'21, SOLE'21, NASMES'21, IIOC'21, EEA-ESEM'20, SED'20, GCER Alumni Conference'20, Midwest Macro'20, 3rd GW Student Research Conference in Economics'20, XII. Winter Workshop,  YES'18

Abstract: Stock markets play a dual role: help allocate capital by conveying information about firms’ fundamentals and provide liquidity by quickly turning stocks into cash. We propose a trading model in which these two roles are endogenously related: more intensive use of stocks for liquidity affects both the information and the noise about fundamentals contained in prices. We structurally estimate stock price informativeness for several countries and show that it sharply declines when the banking system has trouble providing liquidity. We incorporate this module into a dynamic general equilibrium model to study the real effects of this mechanism through capital misallocation across heterogeneous firms. Calibrating the model for the US, we show that, due to less informative stock markets, the output loss is 43% larger if recessions are accompanied by liquidity distress.

Abstract: Recent empirical work shows a strong positive correlation between job-to-job transition rates and nominal wage growth in the U.S. First, using time series regressions, structural monetary policy shocks, and survey data on search effort we provide evidence that inflationary shocks cause higher job-to-job transitions in the subsequent years. Second, to understand the aggregate implications, we build a structural model with aggregate shocks and competitive on-the-job search in which wages react sluggishly to inflation. In periods with high inflation, the decline in real wages incentivizes the employees to search on-the-job more actively, to negotiate a new contract, but also to be less selective in their search behavior. This creates a fundamental trade-off: increased search effort leads to more job-to-job transitions while being less selective reduces the expected efficiency gain in each transition. Therefore, the effect on output becomes ambiguous. Third, we calibrate the model to the U.S. economy and confirm that the output response to inflation shock is non-monotonic. Importantly, our paper highlights a novel role for inflation: the monetary authority can stimulate productivity with an inflationary shock through job-to-job transitions.

Presented at: Banxico, Macro Lunch Talk at UPenn 2018, 2019

Abstract: Negative advertising provides information about the weaknesses of a competitor's product. We study negative advertising with a focus on how its regulation impacts product positioning for profit-maximizing firms. We build a model of informative advertising competition, where product positioning is endogenous and consumers have rational expectations. We show that despite the informational benefits of negative advertising, permitting it (as the Federal Trade Commission in the United States does) may lead to reduced product differentiation and lower consumer welfare, even in markets where firms do not utilize negative advertising in equilibrium. We then extend our model to political competition, where a candidate's objective is to obtain a larger share of votes than the competitor. We show that political competition supports higher positional differentiation, along with more negative advertising than product competition, in line with the observed high use of negative advertising in political races and their rarer use in product competition.  

This paper estimates the global network structure of sovereign credit risk by applying the Diebold-Yilmaz connectedness methodology on sovereign credit default swaps (SCDSs). The level of credit risk connectedness among sovereigns, which is quite high, is comparable to the connectedness among stock markets and foreign exchange markets. In the aftermath of the recent financial crises that originated in developed countries, emerging market countries have played a crucial role in the transmission of sovereign credit risk, while developed countries and debt-ridden developing countries played marginal roles. Secondary regressions show that both trade and capital flows are important determinants of pairwise connectedness across countries. The capital flows became increasingly important after 2013, while the effect of trade flows decreased during the crisis and did not recover afterwards.

Presented at: Financial Globalization and Its Spillovers Workshop at TH Koln and Maastricht University (2017), the Third Economic Networks and Finance Conference at the London School of Economics (2015) and the Second Vienna Workshop on High Dimensional Time Series in Macroeconomics and Finance (2015)