Using the universe of high school and college admissions data in Croatia, we geocoded nearly half a million students’ residential addresses to investigate how their college and major choices are influenced by older neighbors and peers. Using an RDD to exploit time and program variation in admission cutoffs, we find that having an older neighbor who was admitted to and enrolled in a program increases a student’s probability of applying to the program by about 20%. We find that this effect consistently holds only for the closest neighbors, both in terms of distance and age difference. Female students are more likely to be influenced by older neighbors’ choices, and male older neighbors’ admission has a larger impact on both male and female students compared to female older neighbors. The effect is stronger if the student-neighbor pair lives in a region that does not have its own university, implying that the value of information in rural areas is higher. We find evidence that students don’t follow their older neighbors to less competitive programs; instead, they are more likely to apply for the same programs their older neighbors were admitted to when the program is more prestigious. Next, we utilize the variation in weight scheme of Croatia’s college study programs to show evidence, beyond college choices, of how older neighbors affect the human capital formation of their younger peers. The main channel through which we observe this effect is during high school, through specialization in the subjects needed to gain admittance to older neighbors’ college programs. These findings shed light on the intricate dynamics shaping educational decisions and underscores the significant role older neighbors play in guiding younger peers toward specific academic pathways.

We investigate how optimal attention allocation of green-motivated investors changes information asymmetry in financial markets and thus affects firms‘ financing costs. To guide our empirical analysis, we propose a model where investors with heterogeneous green preferences endogenously allocate limited attention to learn market-level or firm-specific fundamental shocks. We find that a higher fraction of green investors in the market leads to higher aggregate attention to green firms. This reduces the information asymmetry of green firms, leading to higher price informativeness and lower leverage. Moreover, the information asymmetry of brown firms and the market increases with the share of green investors. Therefore, greater green attention is associated with less market efficiency. We provide empirical evidence to support our model predictions using U.S. data. Our paper shows how the growing demand for sustainable investing shifts investors‘ attention and benefits eco-friendly firms.

Modigliani and Miller showed the market value of the company is independent of its capital structure, and suggested that dividend policy makes no difference to this law of one price. We experimentally test the Modigliani-Miller theorem in a complete market with two simultaneously traded assets, employing two experimental treatment variations. The first variation involves the dividend stream. According to this variation the dividend payment order is either identical or independent. The second variation involves the market participation, or not, of an algorithmic arbitrageur. We find that Modigliani-Miller’s law of one price can be supported on average with or without an arbitrageur when dividends are identical. The law of one price breaks down when dividend payment order is independent unless there is arbitrageur participation.