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This chapter assesses the volatility spillover from US monetary policy consequent upon the onset of three episodes primarily engineered by the US Fed, namely quantitative easing 1, taper tantrum and balance sheet normalization (BSN) to select emerging market economies (Brazil, India, Russia, South Africa and Turkey) considering around six months pre- and post-occurrence of these events. AR(k)-GARCH (p,q) framework has been used to assess the spillover effect influencing the return of the financial assets and trekking to their volatility segregated as news and persistence effect across markets and economies under study. The authors find that at the overall level, news impact significantly enhanced volatility of bond and currency markets, however, less impact was observed owing to the onset of BSN announcement as markets had factored the news through the well-articulated forward guidance of the Fed.

This chapter examines the long-run and short-run spillover effects of US quantitative easing (QE) on the money market in India. The study adopts the autoregressive distributed lag bounds testing co-integration approach for monthly data from September 2008 to May 2019 to investigate the spillover impact. The results reveal that a 10% rise in US QE led to a 25 bps softening of the weighted average call rate and a 2–5 bps hardening of the Treasury Bill. This impact was beyond the active participation by the Reserve Bank of India on the policy rate and liquidity in the system during the QE episodes. It suggests that the Indian money market is susceptible to US QE.

Over the past four decades, real values of farm real estate and the share of assets on farmers’ balance sheets attributed to farm real estate have increased. The purpose of this paper is to examine the factors that explain the concentration of the US agricultural balance sheet around a particular asset, farm real estate, and the extent to which the degree of asset concentration varies across United States Department of Agriculture production regions.

State-level data from 48 states and entropy-based inequality measures are used to examine changes in asset distributions (real estate vs non-real estate assets) both within and between regions over time.

The agricultural balance sheet is found to concentrate into real estate in the USA over the period 1960-2003 with the rate of concentration varying across production regions. In some regions, the concentration is mainly due to changes in real estate prices, while in other regions concentration is also driven by changes in real estate holdings or changes in total factor productivity.

This study formally estimates the degree to which the concentration of balance sheet items can be explained by the observed changes in farm real estate prices relative to observed changes in agricultural factor productivity or changes in farm real estate holdings. The computed regional differences in asset concentration and its main drivers have implications for changes in equity and solvency positions of farmers as well as agricultural lenders’ risk exposure.

This paper aims to investigate the links between accounting values in Chinese listed companies’ balance sheets and the exposure of their fraudulent activities.

Every balance sheet account is proposed to be a potential vehicle to manipulate financial statements.

Other receivables, inventories, prepaid expenses, employee benefits payables and long-term payables are important indicators of fraudulent financial statements. These results confirm that asset account manipulation is frequently carried out and cast doubt on earlier conclusions by researchers that inflation of liabilities is the most common source of financial statement manipulation.

Previous practices of solely scaling balance sheet values by assets are revealed to produce spurious relationships, while scaling by both assets and sales effectively detects fraudulent financial statements and provides a useful fraud prediction tool for Chinese auditors, regulators and investors.

I build on a strong foundation of prior studies about expatriate compensation in general to provide an overview of changes in expatriate compensation, from home- to host-based approaches, during the past 10 years.

Underpinned by findings from academic and practitioner literature, I review and integrate studies of expatriate compensation and global talent management to outline the challenges and opportunities home- and host-based compensation approaches present to MNEs.

Home-based compensation is becoming an outdated and overly expensive model that is often ineffective in moving MNEs’ global competitive advantage to where it needs to be, leaving host-based approaches as the only alternative. But the use of host-based “cheaper” compensation approaches can also lead to unintended outcomes for MNEs in terms of unforeseen opportunity costs (such as the loss of critical talent) arising from shortsighted compensation decisions.

I argue that expatriate compensation works best when it is not based on an employees’ home-country status but instead on the role that he or she performs locally. I suggest a host-based compensation approach — global compensation — that is based on the worth of the position rather than where the individual has come from. Such an approach is more equitable because it is performance-based thereby eliminating overpaying and perceived unfairness. It is much simpler to administer than home-based compensation because it represents an extension of most MNEs already existing domestic (home country) pay-for-performance model.

Despite more than 10 years of new compensation practices being implemented and reported by global mobility practitioners, very little has been studied or written by scholars about some of the recent changes in expatriate compensation over the past decade. The chapter addresses this gap in academic literature.